📜 Post with us on Reddit
📝 Create a new article
🏭 Create a company page
🇬🇧 - in English
🇫🇷 - en Français (FR)
🇵🇹 - em Português (PT)
🇩🇪 - auf Deutsch (DE)
🇯🇵 - 日本語で (JA)
Sponsored articles

You can edit almost every page by Creating an account and confirming your email.

Centrality Measures

From EverybodyWiki Bios & Wiki


The most comprehensive centrality measures list.

For each measure the name, reference, abbreviation, publish year and category are specified (if available). This list will be updated regularly.

If use this list please cite our papers as:

Jalili Mahdi, Salehzadeh-Yazdi Ali, et al. (2015) CentiServer: A Comprehensive Resource, Web-Based Application and R Package for Centrality Analysis. PLoS ONE 10(11): e0143111. DOI:10.1371/journal.pone.0143111

Jalili Mahdi, Salehzadeh-Yazdi Ali, et al. (2016) Evolution of centrality measurements for the detection of essential proteins in biological networks. Frontiers in Physiology, 7, p.375. DOI:10.3389/fphys.2016.00375

Alphabetically sorted list

  1. Absorbing Random-walk Centrality [1] 2016
  2. AC-based Power Flow [2] 2017
  3. Adapted PageRank Algorithm Based [3] (APA Based) 2016
  4. Adapted PageRank Algorithm Biplex Centerality [4] (APABI) 2019 Bipartite graph
  5. Adapted PageRank Algorithm [5] (APA) 2012
  6. Adjusted Betweenness Centrality [6] 2012
  7. Agglomeration Centrality [7] 2019
  8. Aggregating Centrality Rankings [8] 2020
  9. Algebraic Centrality [9] 2010
  10. All-subgraphs Centrality [10] 2020
  11. All Cycle Betweenness Centrality [11] (ACC) 2018
  12. Alpha Centrality [12] 2001
  13. Alpha Current-Flow Betweenness Centrality [13] 2013
  14. Annotation Transcriptional Centrality [14] (ATC) 2010 Biological network
  15. Application-based Centrality [15] 2017
  16. Approximating Betweenness Centrality [16] (ABRA) 2018 Dynamic graph
  17. AS hegemony [17] 2017
  18. ATria [18] 2017 Biological network
  19. Attachment Centrality [19] 2016
  20. Average Distance [20] 2009
  21. Bargaining Centrality [21] 1987
  22. Barycenter Centrality 2009
  23. Based on Random Walks Centrality [22] (BORW Centrality) 2019 Bipartite graph
  24. Bayesian Centrality 2014
  25. Beta Current-Flow Betweenness Centrality [23] 2015
  26. Betweenness Centrality [24] 1977
  27. Bi-directional h-index [25] 2018
  28. Biharmonic Distance Related Centrality [26] (BDRC) 2018 Edge centrality, Weighted graph
  29. Bipartivity [27] 2005 Biological network, Bipartite graph
  30. BiRank [28] 2017 Bipartite graph
  31. Bonacich Power Centrality [29] 1987
  32. Bonacich Shapley Centrality [30] 2021
  33. BottleNeck [31] 2004 Biological network
  34. Bounded-Distance Betweenness Centrality [32] 2006
  35. Bow-Tie Centrality [33] 2019 Weighted graph, Directed graph
  36. Bridgeness Centrality [34] 2016
  37. Bridgeness [35] 2008
  38. BridgeRank [36] 2018
  39. Bridging Centrality [37] 2008
  40. Bundle Index [38] 2020
  41. Burt's constraint [39] 2004
  42. C-path Centrality 2016
  43. CCIS [40] 2013 Biological network
  44. Centrality-guided Deep Random Walk [41] 2021
  45. Centroid Value 2009
  46. Change Number of Connected Components [42] (CNCC) 2013 Biological network
  47. Change Number of Maximum Connected Components [43] (CNMCC) 2013 Biological network
  48. Circuit Centrality [44] 2016
  49. Classifying Quality Centrality [45] (CQC) 2018
  50. Closeness Centrality Group Identification [46] 2016
  51. Closeness Centrality [47] 1950
  52. Closeness Vitality [48] 2005
  53. Clustering-Embedded Eigenvector Centrality [49] 2020
  54. ClusterRank [50] 2013
  55. Co-Betweenness Centrality [51] 2009
  56. Co-Expression Weighted by Clustering Coefficient [52] (CoEWC) 2013 Biological network
  57. Co-HITS [53] 2009 Bipartite graph
  58. Cocktail Centrality [54] 2021 Biological network, Combination
  59. Combined Gravity Centrality [55] 2020 Combination
  60. Combined Network Centrality Approach [56] (CNCA) 2021 Combination
  61. Combining of Existing Centrality Measures [57] 2017 Combination
  62. Combining Two-Layers PageRank and APA Centrality [58] 2018
  63. Combining with Tunable Parameters [59] 2008 Combination
  64. Communicability Betweenness Centrality [60] 2009
  65. Communicability Centrality 2008
  66. Community Centrality [61] 2006
  67. Complete Neighbourhood Centrality [62] 2020
  68. Complex Edge and Node Clustering Coefficient [63] (CENC) 2020
  69. Composite Centrality [64] 2014 Edge centrality
  70. Conductance Eigenvector Centrality [65] (CEC) 2016
  71. Connectability to Nodes Within Two Degrees of Separation [66] 2018 Weighted graph
  72. Connectionist Centrality [67] 2013
  73. Consensus-induced Centrality [68] 2018
  74. Content Centrality [69] 2016
  75. Continuous-time Quantum Walks Centrality [70] 2017
  76. Control Centrality [71] 2012
  77. Convex Combinations of Centrality [72] 2020 Combination
  78. Copeland in-degree Index [73] 2020
  79. Coreness Centrality [74] 2014
  80. Covertness Centrality [75] 2012
  81. Critical Flow Centrality [76] (CFC) 2019 Weighted graph
  82. Cross-Clique Connectivity [77] 2013
  83. Cross-Face Centrality [78] 2020
  84. Cross-Layer Betweenness Centrality [79] (CBC) 2016
  85. CS_TOTR [80] 2018 Directed graph, Negative edge
  86. Cumulative Neighboring Relationship [81] (CNR) 2018 Combination
  87. Current-Flow Betweenness Centrality [82] 2005
  88. Current-Flow Closeness Centrality [83] 2005
  89. Cycle-Centrality [84] 2018
  90. Dangalchev Closeness Centrality [85] 2006
  91. Decay Centrality [86] 2008
  92. Degree, Clustering coefficient, Average neighbor degree, Like, Post [87] (DCALP) 2018
  93. Degree-like Centrality [88] 2020
  94. Degree Centrality Negative Ties [89] 2017 Negative edge
  95. Degree Centrality [90] 1741
  96. Degree Deviation Centrality [91] 2017 Dynamic graph
  97. Degree Mass Centrality [92] 2015
  98. Degree Sphere Centrality [93] 2009
  99. DelayFlow Centrality [94] 2013
  100. Density Centrality [95] 2018
  101. Density of Maximum Neighborhood Component [96] (DMNC) 2008
  102. Differentially-Private Two-Party Egocentric Betweenness Centrality [97] 2019
  103. DiffSLC Centrality [98] 2017 Biological network, Combination
  104. Diffusion Centrality [99] (DC) 2016
  105. Diffusion Degree [100] 2011
  106. Disease Flow Centrality [101] (DFC) 2011
  107. Disease Fractional Betweenness [102] (DFB) 2019 Biological network
  108. Distance Entropy [103] 2018
  109. Distinctiveness Centrality [104] 2020 Weighted graph
  110. Distributed Current-Flow Betweenness Centrality [105] 2015
  111. Diverse Centrality [106] 2021
  112. Double Screening Scheme [107] (DSS) 2008
  113. dpc [108] 2020
  114. Dynamic-Sensitive Centrality [109] (DS) 2016
  115. Dynamical Centrality [110] 2017 Dynamic graph
  116. E-I Centrality [111] 2012
  117. Eccentricity Centrality [112] 1995
  118. ECMSim [113] 2019
  119. Edge Betweenness Centrality [114] 2004 Edge centrality
  120. Edge Centrality [115] (Holevo Quantity) 2016 Edge centrality
  121. Edge Disjoint K-path Centrality [116] 2006
  122. Edge Percolated Component [117] (EPC) 2008
  123. Edge Weighted [118] 2014 Biological network, Weighted graph
  124. Effective Distance-Based Centrality [119] (EDBC) 2021
  125. Effective Distance Closeness Centrality [120] (EDCC) 2015
  126. Effectiveness
  127. Effective Resistance Centrality [121] 2020 Edge centrality
  128. Effective User Index [122] (E-User Index) 2015
  129. Efficiency Centrality [123] 2020
  130. Efficiency Centrality [124] 2017
  131. EGC [125] 2014 Biological network
  132. Ego-betweenness Centrality [126] 2017
  133. Ego Betweenness Centrality [127] 2005
  134. Eigenedge [128] 2019 Edge centrality
  135. Eigentrust [129] 2003
  136. Eigenvector Centrality based on the Two-layer Approach PageRank [130] (CVP2f) 2019
  137. Eigenvector Centrality for Multiplex Networks [131] (CVPBI) 2019
  138. Eigenvector Centrality for Networks with Data [132] (CVP) 2019
  139. Eigenvector Centrality 1972
  140. Embedding Centrality [133] 2018
  141. Energy-Based Centrality [134] 2013 Edge centrality
  142. Entropy-Based Centrality [135] 2020
  143. Entropy-Based Centrality [136] 2018 Weighted graph
  144. Entropy Centrality [137] 2008
  145. Epidemic Centrality [138] 2013
  146. EpistasisKatz [139] 2019 Biological network
  147. EpistasisRank [140] 2019 Biological network
  148. Evidence Theory Centrality [141] (ETC) 2020
  149. Expected Force [142] 2015 Biological network
  150. Exponentially-Attenuated-Betweenness Centrality [143] (EABC) 2019
  151. Extended H-index Centrality [144] (EHC) 2019
  152. Extended Mixing H-index Centrality [145] (EMH) 2020
  153. Extended Weighted Degree Centrality [146] (EWD) 2018
  154. Extensity Centrality-Newman [147] (Cext-N) 2014
  155. Flow Betweenness Centrality [148] 1991
  156. Flux Centrality 1993 Biological network
  157. Fragmentation Centrality 2006
  158. Fuzzy Centrality [149] 2017 Combination
  159. Fuzzy Closeness Centrality [150] 2014
  160. Game Centrality [151] 2013
  161. Game Theoretic Centrality [152] 2020 Biological network
  162. Generalized Closeness Index [153] (GCC) 2018
  163. Geo-referenced Eigenvector Centrality [154] 2019
  164. Geodesic K-Path Centrality [155] 2006
  165. Gil Schmidt Power Centrality Index [156] 2009
  166. Gramian-based Edge Centrality [157] 2019 Edge centrality
  167. Graph Fourier Transform Centrality [158] (GFT) 2017
  168. Graphlet Degree Centrality [159] 2011 Biological network
  169. Gravity Centrality Index [160] 2016
  170. Ground-current Centrality [161] 2020
  171. Group-based Centrality [162] 2021
  172. Group Betweenness Centrality [163] 1999
  173. Group Centrality [164] 2019
  174. h-Centrality [165] 2011 Weighted graph
  175. h-Degree Centrality [166] 2011 Weighted graph
  176. H-group Closeness Centrality [167] 2017
  177. H-index Group Centrality [168] 2020
  178. H-Index Mixing Centrality [169] (CHM) 2019
  179. h-index strength [170] 2019
  180. Harary Graph Centrality [171] 1995
  181. Hard Cross Betweenness Centrality [172] (HCBC) 2019
  182. Harmonically-Attenuated-Betweenness Centrality [173] (HABC) 2019
  183. Harmonic Centrality [174] 2000
  184. Heatmap Centrality [175] 2020
  185. HellRank [176] 2017
  186. HITS Based Page Rank [177] 2017
  187. Hubbell Index 1965
  188. Hybrid Degree Centrality [178] 2017 Combination
  189. Hybrid Hierarchical K-shell [179] (HHKS) 2019
  190. Hyperbolic Betweenness Centrality [180] (HBC) 2017
  191. Hyperbolic Traffic Load Centrality [181] (HTLC) 2016
  192. Hypertext Induced Topic Selection [182] (HITS) 1999
  193. Improved Sum of Edge Clustering Coefficient [183] (ISoECC) 2013 Biological network
  194. Incremental Laplacian Centrality [184] 2018
  195. Infection Diffusion Eigenvector Centrality [185] (IDEC) 2014
  196. Information Centrality 1989
  197. Inner Betweenness Centrality [186] (IBC) 2019
  198. Integral k-Shell [187] 2019
  199. Integrated Hubness Score [188] (IHS) 2020 Biological network
  200. Integrated Value of Influence [189] (IVI) 2020
  201. Integration Centrality
  202. Iterative Neighbourinformation Gathering Process [190] (Ing Process) 2017
  203. K-Betweenness Centrality [191] 2006
  204. K-Core Decomposition [192] 1983
  205. k-hop Centrality [193] 2014
  206. K-Path Centrality [194] 2011
  207. K-Path Edge Centrality [195] 2012
  208. K-Shell and Community Centrality [196] (KSC) 2014
  209. K-step Betweenness Centrality [197] 2020
  210. K-step Group Betweenness Centrality [198] 2020
  211. Katz Centrality (Katz Status Index) [199] 1953
  212. KatzR Centrality [200] 2009
  213. Kirchhoff Centrality [201] 2016 Edge centrality
  214. Kleinberg's Centrality [202] 1998
  215. Knotty Centrality [203] 2012
  216. Laplacian Centrality [204] 2012
  217. Laplacian Eigenvector Centrality [205] (LEC) 2017
  218. Ld-PageRank [206] 2018
  219. LeaderRank [207] 2011
  220. Leverage Centrality [208] 2010
  221. Lin Centrality 1976
  222. Linear Threshold Rank [209] (LTR) 2018
  223. Line Electrical Centrality [210] 2019 Edge centrality
  224. Load Centrality [211] 2001
  225. Lobby Index (Centrality) [212] 2009
  226. Local Assortativity [213] (LA) 2008
  227. Local Average Connectivity-Based Method [214] (LAC) 2011 Biological network
  228. Local Bridging Centrality [215] 2016
  229. Local Clustering Coefficient-based Degree Centrality [216] (LCCDC) 2017
  230. Local Clustering Coefficient 1998
  231. Local Clustering H-index Centrality [217] (LCH) 2021
  232. Local Edge Centrality [218] (LEC) 2019
  233. Local Interaction Density [219] (LID) 2015
  234. Local Triangle Centrality [220] (LTC) 2016
  235. Local Triangle Structure Centrality [221] (LTSC) 2019
  236. Local Weighted Centrality [222] (LWC) 2020
  237. Long-Range Interactions Centrality [223] (LRIC) 2016
  238. M-Centrality [224] 2018
  239. m-Ranking [225] 2019 Directed graph
  240. Mapping Entropy Centrality [226] (ME) 2016
  241. Markov Centrality [227] 2003
  242. Maximal Clique Centrality [228] (MCC) 2009
  243. Maximum Influence Degree [229] 2014
  244. Maximum Neighborhood Component [230] (MNC) 2008
  245. Mediation Centrality [231] 2019 Bipartite graph, Negative edge
  246. Meta-Centrality [232] 2016 Biological network, Combination
  247. Mint Centrality [233] 2019
  248. Mixed Gravity Centrality [234] 2018 Combination
  249. Mobility Centrality [235] 2015
  250. Modified Betweenness Centrality [236] 2015
  251. Modified Efficiency Centrality [237] 2019 Weighted graph
  252. Modified Myerson Value Centrality [238] 2021
  253. Modularity-Impact Centrality [239] 2020
  254. Modularity Centrality [240] 2008
  255. Modularity Density Centrality [241] 2010
  256. Motif-Based Centrality [242] 2007 Biological network
  257. Multi-Centrality Index [243] 2019
  258. Multi-parametric Centrality [244] 2018
  259. Multiplex Closeness Centrality [245] (MCC) 2019
  260. Naive Patent Degree [246] 2019 Directed graph
  261. Negative and Positive Effects of Clustering Coefficient [247] 2018
  262. Neighbor Based Centrality [248] 2013
  263. Neighborhood-based Bridge Node Centrality [249] (NBNC) 2021
  264. Neighborhood Closeness Centrality Orthology [250] (NCCO) 2020 Biological network
  265. Neighborhood Closeness Centrality [251] (NCC) 2020 Biological network
  266. Neighborhood Connectivity [252] 2002 Biological network
  267. Neighborhood Coreness VoteRank [253] (NCVoteRank) 2020
  268. Neighborhood Correlation Coefficient [254] 2020 Biological network
  269. Neighborhood Entropy Centrality [255] 2021
  270. Neighborhood Functional Centrality [256] (NFC) 2007 Biological network
  271. Neighborhood Similarity Indicator [257] (LSS) 2017
  272. Net Effect [258] (NE) 2020
  273. Network Centrality [259] (NC) 2012 Biological network
  274. Network Motif Centrality [260] 2014 Biological network
  275. Network Structurally Based Closeness Centrality [261] (NSBCC) 2020
  276. Node-Weighted Centrality [262] 2021 Weighted graph
  277. Node Conductance [263] 2020
  278. Nonbacktracking Centrality [264] 2014
  279. Nonbacktracking Walk Centrality [265] 2018
  280. Normalized Wide Network Ranking Algorithm [266] (NWRank) 2015 Combination, Edge centrality
  281. Normalized α-Centrality [267] (NC) 2011
  282. Opinion Centrality [268] 2017
  283. Overlapping Modular Centrality [269] 2019
  284. p-means Centrality [270] 2019
  285. PageRank 1998
  286. Pairwise Disconnectivity Index [271] 2008 Biological network
  287. Participation-based Betweenness Centrality [272] (PBC) 2020
  288. Partition-aware Closeness Centrality [273] (PaCC) 2019
  289. Partition-aware Geometric Centrality [274] (PaGC) 2019
  290. Partition-aware Harmonic Centrality [275] (PaHC) 2019
  291. Path Operator Calculus [276] (POC) 2019
  292. PCen Centrality [277] 2016
  293. PeC Centrality [278] 2012 Biological network
  294. Percolation Centrality [279] 2013
  295. Personalized Katz [280] 2017
  296. Personalized PageRank [281] 2017
  297. Perturbation Centrality [282] 2013
  298. Physarum Centrality [283] 2019 Biological network, Edge centrality
  299. Pivotal Index [284] 2020
  300. PN Centrality [285] 2014 Negative edge
  301. Political Independence Index [286] (PII) 2014 Negative edge
  302. Popularity-Weighted Content-Based Centrality [287] (P-CBC) 2018
  303. Potential Gain [288] 2019
  304. Preferential Centrality [289] 2019
  305. Principal Component Centrality [290] 2010
  306. Propagation Probability Katz Centrality [291] (PrKatz) 2018
  307. Putative TArget Nodes PrIoritization [292] (PANI) 2011 Biological network
  308. Quantum Centrality [293] 2017
  309. Quantum Hub and Authority Centrality [294] 2021 Bipartite graph, Directed graph
  310. Quasi-Laplacian Centrality [295] 2019
  311. Quasi-stationarity Based Centrality [296] 2010 Directed graph
  312. QuickCent [297] 2019
  313. R0-Adjusted Centrality [298] 2013
  314. Radiality Centrality [299] 1998
  315. Random-Walk Betweenness Centrality [300] 2006
  316. Random-Walk Closeness Centrality [301] 2004
  317. Random Eccentricity [302] 2010
  318. Random Forest based Degree Centrality [303] (RFDC) 2019
  319. Random Tree based Degree Centrality [304] (RTDC) 2019
  320. Random Walk Centrality [305] 2004
  321. Random Walk Decay Centrality [306] 2019
  322. Range-limited Centrality [307] 2012
  323. Rank Centrality [308] 2017
  324. Ranking-Betweenness Centrality [309] 2014
  325. Re-defined Entropy Centrality [310] 2017
  326. Refined Patent Degree [311] 2019 Directed graph
  327. Relative Degree Structural Hole Centrality [312] (RDSH) 2019
  328. Relative Edge Betweenness Centrality [313] 2016 Edge centrality
  329. Relevance-embedding Centrality [314] 2020
  330. Residual Closeness Centrality [315] 2006
  331. Residue Centrality [316] 2006 Biological network
  332. Resilience Centrality [317] 2020
  333. Rumor Centrality [318] 2010
  334. SALSA [319] 2002
  335. Second Order Centrality [320] 2011
  336. Seeley Index 1949
  337. Semi Local Centrality [321] 2012
  338. Shannon-Parry Measure [322] (SPM) 2014
  339. Shell Modulus Centrality 2017
  340. Short-Range Interaction Centrality [323] (SRIC) 2016
  341. Shortest Cycle Closeness Centrality [324] (SCC) 2018
  342. Signless-laplacian Eigenvector Centrality [325] 2021 Edge centrality
  343. Singular Vector of Tensor Centrality [326] (SVT) 2018 Bipartite graph
  344. Sociability Centrality [327] 2016
  345. Social-Relation based Centrality [328] (SoReC) 2019
  346. Soft Cross Betweenness Centrality [329] (SCBC) 2019
  347. Source/Sink Centrality [330] (SSC) 2020 Biological network
  348. Spanning Tree Centrality [331] (STC) 2015 Weighted graph
  349. Spatial Strength Centrality [332] 2020
  350. Spike-based Centrality [333] 2020
  351. Split-and-Transfer Flow Based Entropic Centrality [334] 2019
  352. Spreading Influence Related Centrality [335] 2019
  353. Star Degree Centrality [336] (SDC) 2019 Biological network
  354. Status Measure [337] 2004 Negative edge
  355. Straightness Centrality 2006
  356. Strength (Weighted vertex degree) [338] 2004 Weighted graph
  357. Stress Centrality [339] 1953
  358. Structural Hole Centrality [340] 2020
  359. Structurally Dominant Proteins [341] (SDP) 2014 Biological network, Combination
  360. Subgraph Centrality [342] 2005
  361. Sum of Edge Clustering Coefficient [343] (SoECC) 2011 Biological network
  362. Super Mediator [344] 2016
  363. Targeted Betweenness Centrality [345] 2021
  364. Targetoriented latent link Criticalness Centrality [346] (TCC)
  365. Tempo Centrality [347] 2017
  366. Temporal Dynamic-Sensitive Centrality [348] (TDC) 2017
  367. Temporal Katz Centrality [349] 2018 Dynamic graph
  368. TEO [350] 2018 Biological network
  369. Topological Coefficient [351] 2005 Biological network
  370. Topologically Biased Multiplex PageRank [352] 2018
  371. Topologically Biased Random Walks Centrality [353] (TBRW) 2019 Bipartite graph
  372. Total Effect [354] (TE) 2020
  373. Tr-centrality [355] 2020
  374. Traffic Load Centrality [356] (TLC) 2016
  375. Transmission Centrality [357] 2018 Edge centrality
  376. Trip Centrality [358] 2019
  377. Truncated Alpha Current-Flow Betweenness Centrality [359] 2013
  378. Trust-based Most Influential Node Discovery [360] (TMID) 2019
  379. Trust Transitivity [361] 2011
  380. Tukey Depth Centrality [362] 2021
  381. Tunable Path Centrality [363] (TPC) 2014 Path centrality
  382. TwitterRank [364] 2010
  383. Two-Layers PageRank [365] 2016
  384. United Complex Centrality with Parameter Alpha [366] (UC-P) 2017 Biological network
  385. United Complex Centrality [367] (UC) 2017 Biological network
  386. Versatility Centrality [368] 2015 Bipartite graph
  387. Vertex Centrality [369] (Holevo Quantity) 2017
  388. Vibrational Centrality [370] 2010
  389. ViralRank [371] 2018
  390. VoteRank [372] 2016
  391. w-Lobby Index [373] 2011 Weighted graph
  392. Walk-betweenness [374] 2021
  393. Weighted Community Betweenness Centrality [375] 2018
  394. Weighted Degree Centrality [376] (WDC) 2014 Biological network, Weighted graph
  395. Weighted H-index Centrality [377] 2019 Biological network, Weighted graph
  396. Weighted LeaderRank [378] 2014 Weighted graph
  397. Weighted Sum of Loads Eigenvector Centrality [379] (WSL-EC) 2016 Biological network, Weighted graph
  398. Weight Neighborhood Centrality [380] 2017
  399. Wiener Index Biological network
  400. WVoteRank [381] 2019
  401. X-degree Centrality [382] 2021
  402. X-nonbacktracking Centrality [383] 2021
  403. Θ-Kirchhoff Edge Centrality [384] 2017 Edge centrality, Weighted graph
  404. α-Nonbacktracking Centrality [385] 2019
  405. ρ-Geodesic Betweenness Centrality [386] 2017

References

  1. ↑ Mavroforakis C., Mathioudakis M., Gionis A., 2016. Absorbing random-walk centrality: Theory and algorithms. Proceedings - IEEE International Conference on Data Mining, ICDM, 2016-January, pp.901-906. DOI: 10.1109/ICDM.2015.103
  2. ↑ Li J., Dueñas-Osorio L., Chen C., Shi C., 2017. AC power flow importance measures considering multi-element failures. Reliability Engineering and System Safety, 160, pp.89-97. DOI: 10.1016/j.ress.2016.11.010
  3. ↑ Agryzkov T., Tortosa L., Vicent J., 2016. New highlights and a new centrality measure based on the Adapted PageRank Algorithm for urban networks. Applied Mathematics and Computation, 291, pp.14-29. DOI: 10.1016/j.amc.2016.06.036
  4. ↑ Agryzkov T., Curado M., Pedroche F., Tortosa L., Vicent J.F., 2019. Extending the adapted PageRank algorithm centrality to multiplex networks with data using the PageRank two-layer approach. Symmetry, 11(2). DOI: 10.3390/sym11020284
  5. ↑ Agryzkov T., Oliver J., Tortosa L., Vicent J., 2012. An algorithm for ranking the nodes of an urban network based on the concept of PageRank vector. Applied Mathematics and Computation, 219(4), pp.2186-2193. DOI: 10.1016/j.amc.2012.08.064
  6. ↑ Caporossi, G., Paiva, M., Vukičevic, D. and Segatto, M., 2012. Centrality and betweenness: vertex and edge decomposition of the Wiener index. MATCH-Communications in Mathematical and Computer Chemistry, 68(1), p.293.
  7. ↑ Liu G., Yao X., Luo Z., Kang S., Long W., Fan Q., Gao P., 2019. Agglomeration centrality to examine spatial scaling law in cities. Computers, Environment and Urban Systems, 77. DOI: 10.1016/j.compenvurbsys.2019.101357
  8. ↑ Oliva G., Esposito Amideo A., Starita S., Setola R., Scaparra M.P., 2020. Aggregating centrality rankings: A novel approach to detect critical infrastructure vulnerabilities. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11777 LNCS, pp.57-68. DOI: 10.1007/978-3-030-37670-3_5
  9. ↑ Kirkland S., 2010. Algebraic connectivity for vertex-deleted subgraphs, and a notion of vertex centrality. Discrete Mathematics, 310(4), pp.911-921. DOI: 10.1016/j.disc.2009.10.011
  10. ↑ Riveros C., Salas J., 2020. A family of centrality measures for graph data based on subgraphs. Leibniz International Proceedings in Informatics, LIPIcs, 155. DOI: 10.4230/LIPIcs.ICDT.2020.23
  11. ↑ Zhou X., Liang X., Zhao J., Zhang S., 2018. Cycle Based Network Centrality. Scientific Reports, 8(1). DOI: 10.1038/s41598-018-30249-4
  12. ↑ Bonacich P., Lloyd P., 2001. Eigenvector-like measures of centrality for asymmetric relations. Social Networks, 23(3), pp.191-201. DOI: 10.1016/S0378-8733(01)00038-7
  13. ↑ Avrachenkov K., Litvak N., Medyanikov V., Sokol M., 2013. Alpha current flow betweenness centrality. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8305 LNCS, pp.106-117. DOI: 10.1007/978-3-319-03536-9_9
  14. ↑ Prifti E., Zucker J.D., Clément K., Henegar C., 2010. Interactional and functional centrality in transcriptional co-expression networks. Bioinformatics, 26(24), pp.3083-3089. DOI: 10.1093/bioinformatics/btq591
  15. ↑ Khadangi E., Bagheri A., 2017. Presenting novel application-based centrality measures for finding important users based on their activities and social behavior. Computers in Human Behavior, 73, pp.64-79. DOI: 10.1016/j.chb.2017.03.014
  16. ↑ Riondato M., Upfal E., 2018. ABRA: Approximating betweenness centrality in static and dynamic graphs with rademacher averages. ACM Transactions on Knowledge Discovery from Data, 12(5). DOI: 10.1145/3208351
  17. ↑ Fontugne R., Shah A., Aben E., 2017. AS hegemony: A robust metric for as centrality. SIGCOMM Posters and Demos 2017 - Proceedings of the 2017 SIGCOMM Posters and Demos, Part of SIGCOMM 2017, , pp.48-50. DOI: 10.1145/3123878.3131982
  18. ↑ Cickovski T., Peake E., Aguiar-Pulido V., Narasimhan G., 2017. ATria: A novel centrality algorithm applied to biological networks. BMC Bioinformatics, 18. DOI: 10.1186/s12859-017-1659-z
  19. ↑ Skibski O., Rahwan T., Michalak T., Yokoo M., 2019. Attachment centrality: Measure for connectivity in networks. Artificial Intelligence, 274, pp.151-179. DOI: 10.1016/j.artint.2019.03.002
  20. ↑ del Rio G., Koschützki D., Coello G., 2009. How to identify essential genes from molecular networks?. BMC Systems Biology, 3, pp.102. DOI: 10.1186/1752-0509-3-102
  21. ↑ Bonacich, P., 1987. Power and centrality: A family of measures. American journal of sociology, 92(5), pp.1170-1182. DOI: 10.1086/228631
  22. ↑ Lv L., Zhang K., Bardou D., Zhang T., Zhang J., Cai Y., Jiang T., 2019. A new centrality measure based on random walks for multilayer networks under the framework of tensor computation. Physica A: Statistical Mechanics and its Applications, 526. DOI: 10.1016/j.physa.2019.04.236
  23. ↑ Avrachenkov K., Mazalov V., Tsynguev B., 2015. Beta current flow centrality for weighted networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9197, pp.216-227. DOI: 10.1007/978-3-319-21786-4_19
  24. ↑ Freeman, Linton. 1977. A set of measures of centrality based on betweenness. Sociometry. 40 (1): 35–41. DOI: 10.2307/3033543
  25. ↑ Zhai L., Yan X., Zhang G., 2018. Bi-directional h-index: A new measure of node centrality in weighted and directed networks. Journal of Informetrics, 12(1), pp.299-314. DOI: 10.1016/j.joi.2018.01.004
  26. ↑ Yi, Y., Shan, L., Li, H. and Zhang, Z., 2018, July. Biharmonic distance related centrality for edges in weighted networks. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (pp. 3620-3626).
  27. ↑ Estrada E., Rodríguez-Velázquez J.A., 2005. Spectral measures of bipartivity in complex networks. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 72(4). DOI: 10.1103/PhysRevE.72.046105
  28. ↑ He X., Gao M., Kan M.Y., Wang D., 2017. BiRank: Towards Ranking on Bipartite Graphs. IEEE Transactions on Knowledge and Data Engineering, 29(1), pp.57-71. DOI: 10.1109/TKDE.2016.2611584
  29. ↑ Bonacich, P., 1987. Power and centrality: A family of measures. American journal of sociology, 92(5), pp.1170-1182. DOI: 10.1086/228631
  30. ↑ Allouch, N., Meca, A. and Polotskaya, K., 2021. The Bonacich Shapley centrality. School of Economics, University of Kent.
  31. ↑ Pržulj N., Wigle D., Jurisica I., 2004. Functional topology in a network of protein interactions. Bioinformatics, 20(3), pp.340-348. DOI: 10.1093/bioinformatics/btg415
  32. ↑ Borgatti S., Everett M., 2006. A Graph-theoretic perspective on centrality. Social Networks, 28(4), pp.466-484. DOI: 10.1016/j.socnet.2005.11.005
  33. ↑ Glattfelder J., 2019. THE BOW-TIE CENTRALITY: A NOVEL MEASURE for DIRECTED and WEIGHTED NETWORKS with AN INTRINSIC NODE PROPERTY. Advances in Complex Systems, . DOI: 10.1142/S0219525919500188
  34. ↑ Jensen P., Morini M., Karsai M., Venturini T., Vespignani A., Jacomy M., Cointet J.P., Mercklé P., Fleury E., 2016. Detecting global bridges in networks. Journal of Complex Networks, 4(3), pp.319-329. DOI: 10.1093/comnet/cnv022
  35. ↑ Nepusz T., Petróczi A., Négyessy L., Bazsó F., 2008. Fuzzy communities and the concept of bridgeness in complex networks. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 77(1). DOI: 10.1103/PhysRevE.77.016107
  36. ↑ Salavati C., Abdollahpouri A., Manbari Z., 2018. BridgeRank: A novel fast centrality measure based on local structure of the network. Physica A: Statistical Mechanics and its Applications, 496, pp.635-653. DOI: 10.1016/j.physa.2017.12.087
  37. ↑ Hwang W., Kim T., Ramanathan M., Zhang A., 2008. Bridging centrality: Graph mining from element level to group level. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, , pp.336-344. DOI: 10.1145/1401890.1401934
  38. ↑ Aleskerov F., Roman A., Rezyapova A., Yakuba V., 2020. New Centrality Measures in Networks and their Applications to the International Trade and Migration Networks. Proceedings - IEEE Computer Society\'s Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS, 2020-November. DOI: 10.1109/MASCOTS50786.2020.9285957
  39. ↑ Burt R., 2004. Structural holes and good ideas. American Journal of Sociology, 110(2), pp.349-399. DOI: 10.1086/421787
  40. ↑ Sun H., Liang Y., Chen L., Wang Y., Du W., Shi X., 2013. An improved sum of edge clustering coefficient method for essential protein identification. Journal of Bionanoscience, 7(4), pp.386-390. DOI: 10.1166/jbns.2013.1152
  41. ↑ Chang Y.C., Lai K.T., Chou S.C.T., Chiang W.C., Lin Y.C., 2021. Who is the boss? Identifying key roles in telecom fraud network via centrality-guided deep random walk. Data Technologies and Applications, 55(1), pp.1-18. DOI: 10.1108/DTA-05-2020-0103
  42. ↑ Sun H., Liang Y., Chen L., Wang Y., Du W., Shi X., 2013. An improved sum of edge clustering coefficient method for essential protein identification. Journal of Bionanoscience, 7(4), pp.386-390. DOI: 10.1166/jbns.2013.1152
  43. ↑ Sun H., Liang Y., Chen L., Wang Y., Du W., Shi X., 2013. An improved sum of edge clustering coefficient method for essential protein identification. Journal of Bionanoscience, 7(4), pp.386-390. DOI: 10.1166/jbns.2013.1152
  44. ↑ Zhang, W., 2016. Screening node attributes that significantly influence node centrality in the network. Selforganizology, 3(3), pp.75-86.
  45. ↑ Yao Y., Xiao X., Zhang C., Xia S., 2018. Classifying quality centrality for source localization in social networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10966 LNCS, pp.295-307. DOI: 10.1007/978-3-319-94289-6_19
  46. ↑ Chen C., Wang W., Wang X., 2016. Efficient maximum closeness centrality group identification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9877 LNCS, pp.43-55. DOI: 10.1007/978-3-319-46922-5_4
  47. ↑ Bavelas A., 1950. Communication Patterns in Task-Oriented Groups. Journal of the Acoustical Society of America, 22(6), pp.725-730. DOI: 10.1121/1.1906679
  48. ↑ Brandes, U., 2005. Network analysis: methodological foundations (Vol. 3418). Springer Science & Business Media.
  49. ↑ Carrizosa E., Marin A., Pelegrin M., 2020. Spotting Key Members in Networks: Clustering-Embedded Eigenvector Centrality. IEEE Systems Journal, 14(3), pp.3916-3925. DOI: 10.1109/JSYST.2020.2982266
  50. ↑ Chen D.B., Gao H., Lü L., Zhou T., 2013. Identifying influential nodes in large-scale directed networks: The role of clustering. PLoS ONE, 8(10). DOI: 10.1371/journal.pone.0077455
  51. ↑ Kolaczyk E., Chua D., Barthélemy M., 2009. Group betweenness and co-betweenness: Inter-related notions of coalition centrality. Social Networks, 31(3), pp.190-203. DOI: 10.1016/j.socnet.2009.02.003
  52. ↑ Zhang X., Xu J., Xiao W.x., 2013. A New Method for the Discovery of Essential Proteins. PLoS ONE, 8(3). DOI: 10.1371/journal.pone.0058763
  53. ↑ Deng H., Lyu M., King I., 2009. A generalized Co-HITS algorithm and its application to bipartite graphs. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, , pp.239-247. DOI: 10.1145/1557019.1557051
  54. ↑ Gouveia C., Móréh Á., Jordán F., 2021. Combining centrality indices: Maximizing the predictability of keystone species in food webs. Ecological Indicators, 126. DOI: 10.1016/j.ecolind.2021.107617
  55. ↑ Şimşek M., Meyerhenke H., 2020. Combined centrality measures for an improved characterization of influence spread in social networks. Journal of Complex Networks, 8(1). DOI: 10.1093/comnet/cnz048
  56. ↑ Das A., Biswas A., 2021. Rumor Source Identification on Social Networks: A Combined Network Centrality Approach. Advances in Intelligent Systems and Computing, 1299 AISC, pp.269-280. DOI: 10.1007/978-981-33-4299-6_22
  57. ↑ Fei L., Mo H., Deng Y., 2017. A new method to identify influential nodes based on combining of existing centrality measures. Modern Physics Letters B, 31(26). DOI: 10.1142/S0217984917502438
  58. ↑ Agryzkov T., Pedroche F., Tortosa L., Vicent J.F., 2018. Combining the two-layers pageRank approach with the APA centrality in networks with data. ISPRS International Journal of Geo-Information, 7(12). DOI: 10.3390/ijgi7120480
  59. ↑ Jianwei W., Lili R., Tianzhu G., 2008. A new measure of node importance in complex networks with tunable parameters. 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, . DOI: 10.1109/WiCom.2008.1170
  60. ↑ Estrada E., Higham D.J., Hatano N., 2009. Communicability betweenness in complex networks. Physica A: Statistical Mechanics and its Applications, 388(5), pp.764-774. DOI: 10.1016/j.physa.2008.11.011
  61. ↑ Newman M.E.J., 2006. Finding community structure in networks using the eigenvectors of matrices. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 74(3). DOI: 10.1103/PhysRevE.74.036104
  62. ↑ Das K., Samanta S., De K., Pal M., 2020. Complete neighbourhood centrality and its application. 4th International Conference on Computational Intelligence and Networks, CINE 2020, . DOI: 10.1109/CINE48825.2020.234386
  63. ↑ Lu P., Yu J.J., 2020. A mixed clustering coefficient centrality for identifying essential proteins. International Journal of Modern Physics B, 34(10). DOI: 10.1142/S0217979220500903
  64. ↑ Joseph A., Chen G., 2014. Composite centrality: A natural scale for complex evolving networks. Physica D: Nonlinear Phenomena, 267, pp.58-67. DOI: 10.1016/j.physd.2013.08.005
  65. ↑ Li X., Liu Y., Jiang Y., Liu X., 2016. Identifying social influence in complex networks: A novel conductance eigenvector centrality model. Neurocomputing, 210, pp.141-154. DOI: 10.1016/j.neucom.2015.11.123
  66. ↑ Amano S., Ogawa K., Miyake Y., 2018. Node property of weighted networks considering connectability to nodes within two degrees of separation. Scientific Reports, 8(1). DOI: 10.1038/s41598-018-26781-y
  67. ↑ Wang Q., Yu X., Zhang X., 2013. A connectionist model-based approach to centrality discovery in social networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8178 LNAI, pp.82-94. DOI: 10.1007/978-3-319-04048-6_8
  68. ↑ Gao, S. and Caines, P.E., 2018, July. Consensus-induced Centrality for Networks of Dynamical Systems. In Proceedings of the 23rd International Symposium on Mathematical Theory of Networks and Systems, Hong Kong, China (pp. 769-775).
  69. ↑ Fushimi T., Satoh T., Saito K., Kazama K., Kando N., 2016. Content centrality measure for networks: Introducing distance-based Decay weights. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10047 LNCS, pp.40-54. DOI: 10.1007/978-3-319-47874-6_4
  70. ↑ Izaac J.A., Zhan X., Bian Z., Wang K., Li J., Wang J.B., Xue P., 2017. Centrality measure based on continuous-time quantum walks and experimental realization. Physical Review A, 95(3). DOI: 10.1103/PhysRevA.95.032318
  71. ↑ Liu Y., Slotine J., Barabási A., 2012. Control Centrality and Hierarchical Structure in Complex Networks. PLoS ONE, 7(9). DOI: 10.1371/journal.pone.0044459
  72. ↑ Keng Y.Y., Kwa K.H., McClain C., 2020. Convex combinations of centrality measures. Journal of Mathematical Sociology, . DOI: 10.1080/0022250X.2020.1765776
  73. ↑ Aleskerov F., Roman A., Rezyapova A., Yakuba V., 2020. New Centrality Measures in Networks and their Applications to the International Trade and Migration Networks. Proceedings - IEEE Computer Society\'s Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS, 2020-November. DOI: 10.1109/MASCOTS50786.2020.9285957
  74. ↑ Bae J., Kim S., 2014. Identifying and ranking influential spreaders in complex networks by neighborhood coreness. Physica A: Statistical Mechanics and its Applications, 395, pp.549-559. DOI: 10.1016/j.physa.2013.10.047
  75. ↑ Ovelgönne M., Kang C., Sawant A., Subrahmanian V., 2012. Covertness centrality in networks. Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, , pp.863-870. DOI: 10.1109/ASONAM.2012.156
  76. ↑ Williams, J., 2019. Identifying sensitive components in infrastructure networks via critical flows. engrXiv.
  77. ↑ Faghani M., Nguyen U., 2013. A study of xss worm propagation and detection mechanisms in online social networks. IEEE Transactions on Information Forensics and Security, 8(11), pp.1815-1826. DOI: 10.1109/TIFS.2013.2280884
  78. ↑ Ibrahim M.H., Missaoui R., Vaillancourt J., 2020. Cross-Face Centrality: A New Measure for Identifying Key Nodes in Networks Based on Formal Concept Analysis. IEEE Access, 8, pp.206901-206913. DOI: 10.1109/ACCESS.2020.3038306
  79. ↑ Chakraborty T., Narayanam R., 2016. Cross-layer betweenness centrality in multiplex networks with applications. 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016, , pp.397-408. DOI: 10.1109/ICDE.2016.7498257
  80. ↑ Ma Y., Liu M., Zhang P., Qi X., 2018. CS-TOTR: A new vertex centrality method for directed signed networks based on status theory. International Journal of Modern Physics C, 29(5). DOI: 10.1142/S0129183118400028
  81. ↑ Zhou H., Ruan M., Zhu C., Leung V.C.M., Xu S., Huang C.M., 2018. A Time-Ordered Aggregation Model-Based Centrality Metric for Mobile Social Networks. IEEE Access, 6, pp.25588-25599. DOI: 10.1109/ACCESS.2018.2831247
  82. ↑ Brandes U., Fleischer D., 2005. Centrality measures based on current flow. Lecture Notes in Computer Science, 3404, pp.533-544. DOI: 10.1007/978-3-540-31856-9_44
  83. ↑ Brandes U., Fleischer D., 2005. Centrality measures based on current flow. Lecture Notes in Computer Science, 3404, pp.533-544. DOI: 10.1007/978-3-540-31856-9_44
  84. ↑ Giscard P., Wilson R., 2018. Cycle-centrality in economic and biological networks. Studies in Computational Intelligence, 689, pp.14-28. DOI: 10.1007/978-3-319-72150-7_2
  85. ↑ Dangalchev C., 2006. Residual closeness in networks. Physica A: Statistical Mechanics and its Applications, 365(2), pp.556-564. DOI: 10.1016/j.physa.2005.12.020
  86. ↑ Jackson, M. O. 2008. Social and economic networks, volume 3. Princeton university press.
  87. ↑ Forouzandeh S., Sheikhahmadi A., Rezaei Aghdam A., Xu S., 2018. New centrality measure for nodes based on user social status and behavior on Facebook. International Journal of Web Information Systems, 14(2), pp.158-176. DOI: 10.1108/IJWIS-07-2017-0053
  88. ↑ Fan M., Cao Z., Cheng J., Yang F., Qi X., 2020. Degree-like centrality with structural zeroes or ones: When is a neighbor not a neighbor?. Social Networks, 63, pp.38-46. DOI: 10.1016/j.socnet.2020.05.002
  89. ↑ Kaur M., Singh S., 2017. Ranking based comparative analysis of graph centrality measures to detect negative nodes in online social networks. Journal of Computational Science, 23, pp.91-108. DOI: 10.1016/j.jocs.2017.10.018
  90. ↑ Euler, L., 1741. Solutio problematis ad geometriam situs pertinentis. Commentarii academiae scientiarum Petropolitanae, pp.128-140.
  91. ↑ Wang Z., Pei X., Wang Y., Yao Y., 2017. Ranking the key nodes with temporal degree deviation centrality on complex networks. Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017, , pp.1484-1489. DOI: 10.1109/CCDC.2017.7978752
  92. ↑ Li C., Li Q., Van Mieghem P., Stanley H.E., Wang H., 2015. Correlation between centrality metrics and their application to the opinion model. European Physical Journal B, 88(3), pp.1-13. DOI: 10.1140/epjb/e2015-50671-y
  93. ↑ del Rio G., Koschützki D., Coello G., 2009. How to identify essential genes from molecular networks?. BMC Systems Biology, 3, pp.102. DOI: 10.1186/1752-0509-3-102
  94. ↑ Cheng Y., Lee R., Lim E., Zhu F., 2013. DelayFlow centrality for identifying critical nodes in transportation networks. Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, , pp.1462-1463. DOI: 10.1145/2492517.2492595
  95. ↑ Ibnoulouafi A., El Haziti M., 2018. Density centrality: identifying influential nodes based on area density formula. Chaos, Solitons and Fractals, 114, pp.69-80. DOI: 10.1016/j.chaos.2018.06.022
  96. ↑ Lin C., Chin C., Wu H., Chen S., Ho C., Ko M., 2008. Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology.. Nucleic acids research, 36(Web Server issue). DOI: 10.1093/nar/gkn257
  97. ↑ Roohi L., Rubinstein B.I.P., Teague V., 2019. Differentially-Private Two-Party Egocentric Betweenness Centrality. Proceedings - IEEE INFOCOM, 2019-April(), pp.2233-2241. DOI: 10.1109/INFOCOM.2019.8737405
  98. ↑ Mistry D., Wise R.P., Dickerson J.A., 2017. DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network. PLoS ONE, 12(11). DOI: 10.1371/journal.pone.0187091
  99. ↑ Kang C., Kraus S., Molinaro C., Spezzano F., Subrahmanian V., 2016. Diffusion centrality: A paradigm to maximize spread in social networks. Artificial Intelligence, 239, pp.70-96. DOI: 10.1016/j.artint.2016.06.008
  100. ↑ Kundu S., Murthy C., Pal S., 2011. A new centrality measure for influence maximization in social networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6744 LNCS, pp.242-247. DOI: 10.1007/978-3-642-21786-9_40
  101. ↑ Natale F., Savini L., Giovannini A., Calistri P., Candeloro L., Fiore G., 2011. Evaluation of risk and vulnerability using a Disease Flow Centrality measure in dynamic cattle trade networks. Preventive Veterinary Medicine, 98(2-3), pp.111-118. DOI: 10.1016/j.prevetmed.2010.11.013
  102. ↑ Park J., Hescott B.J., Slonim D.K., 2019. Pathway centrality in protein interaction networks identifies putative functional mediating pathways in pulmonary disease. Scientific Reports, 9(1). DOI: 10.1038/s41598-019-42299-3
  103. ↑ Stella M., De Domenico M., 2018. Distance entropy cartography characterises centrality in complex networks. Entropy, 20(4). DOI: 10.3390/e20040268
  104. ↑ Fronzetti Colladon A., Naldi M., 2020. Distinctiveness centrality in social networks. PLoS ONE, 15(5). DOI: 10.1371/journal.pone.0233276
  105. ↑ Lulli A., Ricci L., Carlini E., Dazzi P., 2015. Distributed Current Flow Betweenness Centrality. International Conference on Self-Adaptive and Self-Organizing Systems, SASO, 2015-October, pp.71-80. DOI: 10.1109/SASO.2015.15
  106. ↑ Lyu L., Fain B., Munagala K., Wang K., 2021. Centrality with Diversity. WSDM 2021 - Proceedings of the 14th ACM International Conference on Web Search and Data Mining, , pp.644-652. DOI: 10.1145/3437963.3441789
  107. ↑ Lin C., Chin C., Wu H., Chen S., Ho C., Ko M., 2008. Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology.. Nucleic acids research, 36(Web Server issue). DOI: 10.1093/nar/gkn257
  108. ↑ Chen G., Zhou S., Liu J., Li M., Zhou Q., 2020. Influential node detection of social networks based on network invulnerability. Physics Letters, Section A: General, Atomic and Solid State Physics, 384(34). DOI: 10.1016/j.physleta.2020.126879
  109. ↑ Liu J., Lin J., Guo Q., Zhou T., 2016. Locating influential nodes via dynamics-sensitive centrality. Scientific Reports, 6. DOI: 10.1038/srep21380
  110. ↑ Guo L., Zhang W.Y., Luo Z.J., Gao F.J., Zhang Y.C., 2017. A dynamical approach to identify vertices′ centrality in complex networks. Physics Letters, Section A: General, Atomic and Solid State Physics, 381(48), pp.3972-3977. DOI: 10.1016/j.physleta.2017.10.033
  111. ↑ Everett M., Borgatti S., 2012. Categorical attribute based centrality: E-I and G-F centrality. Social Networks, 34(4), pp.562-569. DOI: 10.1016/j.socnet.2012.06.002
  112. ↑ Hage P., Harary F., 1995. Eccentricity and centrality in networks. Social Networks, 17(1), pp.57-63. DOI: 10.1016/0378-8733(94)00248-9
  113. ↑ Lv L., Zhang K., Zhang T., Li X., Zhang J., Xue W., 2019. Eigenvector centrality measure based on node similarity for multilayer and temporal networks. IEEE Access, 7, pp.115725-115733. DOI: 10.1109/ACCESS.2019.2936217
  114. ↑ Newman M.E.J., Girvan M., 2004. Finding and evaluating community structure in networks. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 69(2 2). DOI: 10.1103/PhysRevE.69.026113
  115. ↑ Lockhart J., Minello G., Rossi L., Severini S., Torsello A., 2016. Edge centrality via the Holevo quantity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10029 LNCS, pp.143-152. DOI: 10.1007/978-3-319-49055-7_13
  116. ↑ Borgatti S., Everett M., 2006. A Graph-theoretic perspective on centrality. Social Networks, 28(4), pp.466-484. DOI: 10.1016/j.socnet.2005.11.005
  117. ↑ Lin C., Chin C., Wu H., Chen S., Ho C., Ko M., 2008. Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology.. Nucleic acids research, 36(Web Server issue). DOI: 10.1093/nar/gkn257
  118. ↑ Wang Y., Sun H., Du W., Blanzieri E., Viero G., Xu Y., Liang Y., 2014. Identification of essential proteins based on ranking Edge-Weights in Protein-Protein Interaction networks. PLoS ONE, 9(9). DOI: 10.1371/journal.pone.0108716
  119. ↑ Ullah A., Wang B., Sheng J., Long J., Khan N., 2021. Identification of Influential Nodes via Effective Distance-based Centrality Mechanism in Complex Networks. Complexity, 2021. DOI: 10.1155/2021/8403738
  120. ↑ Du, Y., Gao, C., Chen, X., Hu, Y., Sadiq, R. and Deng, Y., 2015. A new closeness centrality measure via effective distance in complex networks. Chaos: An Interdisciplinary Journal of Nonlinear Science, 25(3), p.033112. DOI: 10.1063/1.4916215
  121. ↑ Clemente G.P., Cornaro A., 2020. A novel measure of edge and vertex centrality for assessing robustness in complex networks. Soft Computing, 24(18), pp.13687-13704. DOI: 10.1007/s00500-019-04470-w
  122. ↑ Yazici, M. and Sarac, M., 2015. Centrality measures with a new index called E-User (Effective User) Index for determiningthe most effective user in Twitter Online Social Network. International Journal on Computer Science and Engineering, 7(1), p.1.
  123. ↑ P. Marjai, A. Kiss., 2020, Efficiency centrality in time-varying graphs. Acta Universitatis Sapientiae, Informatica, 12, 1, 5−21. DOI: 10.2478/ausi-2020-0001
  124. ↑ Wang S., Du Y., Deng Y., 2017. A new measure of identifying influential nodes: Efficiency centrality. Communications in Nonlinear Science and Numerical Simulation, 47, pp.151-163. DOI: 10.1016/j.cnsns.2016.11.008
  125. ↑ Luo J., Zhang N., 2014. Prediction of Essential Proteins Based On Edge Clustering Coefficient and Gene Ontology Information. Journal of Biological Systems, 22(3), pp.339-351. DOI: 10.1142/S0218339014500119
  126. ↑ Ghanem M., Coriat F., Tabourier L., 2017. Ego-betweenness centrality in link streams. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017, , pp.667-674. DOI: 10.1145/3110025.3110158
  127. ↑ Everett M., Borgatti S.P., 2005. Ego network betweenness. Social Networks, 27(1), pp.31-38. DOI: 10.1016/j.socnet.2004.11.007
  128. ↑ Huang X., Huang W., 2019. Eigenedge: A measure of edge centrality for big graph exploration. Journal of Computer Languages, 55. DOI: 10.1016/j.cola.2019.100925
  129. ↑ Kamvar S., Schlosser M., Garcia-Molina H., 2003. The EigenTrust algorithm for reputation management in P2P networks. Proceedings of the 12th International Conference on World Wide Web, WWW 2003, , pp.640-651. DOI: 10.1145/775152.775242
  130. ↑ Pedroche F., Tortosa L., Vicent J.F., 2019. An eigenvector centrality for multiplex networks with data. Symmetry, 11(6). DOI: 10.3390/sym11060763
  131. ↑ Pedroche F., Tortosa L., Vicent J.F., 2019. An eigenvector centrality for multiplex networks with data. Symmetry, 11(6). DOI: 10.3390/sym11060763
  132. ↑ Pedroche F., Tortosa L., Vicent J.F., 2019. An eigenvector centrality for multiplex networks with data. Symmetry, 11(6). DOI: 10.3390/sym11060763
  133. ↑ Puzis R., Sofer Z., Cohen D., Hugi M., 2018. Embedding-centrality: Generic centrality computation using neural networks. Springer Proceedings in Complexity, (219279), pp.87-97. DOI: 10.1007/978-3-319-73198-8_8
  134. ↑ Kong, R., Han, C., Guo, T. and Pei, W., 2013. An Energy-Based Centrality for Electrical Networks. Energy and Power Engineering, 5(04), p.597. DOI: 10.4236/epe.2013.54B115
  135. ↑ Ni C., Yang J., Kong D., 2020. Sequential seeding strategy for social influence diffusion with improved entropy-based centrality. Physica A: Statistical Mechanics and its Applications, 545. DOI: 10.1016/j.physa.2019.123659
  136. ↑ Qiao T., Shan W., Yu G., Liu C., 2018. A novel entropy-based centrality approach for identifying vital nodes in weighted networks. Entropy, 20(4). DOI: 10.3390/e20040261
  137. ↑ Ortiz-Arroyo D., Hussain D., 2008. An information theory approach to identify sets of key players. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5376 LNCS, pp.15-26. DOI: 10.1007/978-3-540-89900-6_5
  138. ↑ Šikić M., Lančić A., Antulov-Fantulin N., Štefančić H., 2013. Epidemic centrality - Is there an underestimated epidemic impact of network peripheral nodes?. European Physical Journal B, 86(10). DOI: 10.1140/epjb/e2013-31025-5
  139. ↑ Parvandeh S., McKinney B.A., 2019. Epistasisrank and Epistasiskatz: Interaction network centrality methods that integrate prior knowledge networks. Bioinformatics, 35(13), pp.2329-2331. DOI: 10.1093/bioinformatics/bty965
  140. ↑ Parvandeh S., McKinney B.A., 2019. Epistasisrank and Epistasiskatz: Interaction network centrality methods that integrate prior knowledge networks. Bioinformatics, 35(13), pp.2329-2331. DOI: 10.1093/bioinformatics/bty965
  141. ↑ Zhao J., Song Y., Deng Y., 2020. A novel model to identify the influential nodes: Evidence theory centrality. IEEE Access, 8, pp.46773-46780. DOI: 10.1109/ACCESS.2020.2978142
  142. ↑ Lawyer G., 2015. Understanding the influence of all nodes in a network. Scientific Reports, 5. DOI: 10.1038/srep08665
  143. ↑ Singh A., Singh R., Iyengar S., 2019. Hybrid centrality measures for service coverage problem. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11917 LNCS, pp.81-94. DOI: 10.1007/978-3-030-34980-6_11
  144. ↑ Zareie A., Sheikhahmadi A., 2019. EHC: Extended H-index Centrality measure for identification of users’ spreading influence in complex networks. Physica A: Statistical Mechanics and its Applications, 514, pp.141-155. DOI: 10.1016/j.physa.2018.09.064
  145. ↑ Lu P., Dong C., 2020. EMH: Extended Mixing H-index centrality for identification important users in social networks based on neighborhood diversity. Modern Physics Letters B, 34(26). DOI: 10.1142/S021798492050284X
  146. ↑ Yang F., Li X., Xu Y., Liu X., Wang J., Zhang Y., Zhang R., Yao Y., 2018. Ranking the spreading influence of nodes in complex networks: An extended weighted degree centrality based on a remaining minimum degree decomposition. Physics Letters, Section A: General, Atomic and Solid State Physics, 382(34), pp.2361-2371. DOI: 10.1016/j.physleta.2018.05.032
  147. ↑ Zhang G., Liu L., Feng Y., Shao Z., Li Y., 2014. Cext-N index: a network node centrality measure for collaborative relationship distribution. Scientometrics, 101(1), pp.291-307. DOI: 10.1007/s11192-014-1358-8
  148. ↑ Freeman L., Borgatti S., White D., 1991. Centrality in valued graphs: A measure of betweenness based on network flow. Social Networks, 13(2), pp.141-154. DOI: 10.1016/0378-8733(91)90017-N
  149. ↑ Tavassoli S., Zweig K.A., 2017. Fuzzy centrality evaluation in complex and multiplex networks. Springer Proceedings in Complexity, , pp.31-43. DOI: 10.1007/978-3-319-54241-6_3
  150. ↑ Davidsen S., Padmavathamma M., 2014. A fuzzy closeness centrality using andness-direction to control degree of closeness. 1st International Conference on Networks and Soft Computing, ICNSC 2014 - Proceedings, , pp.203-208. DOI: 10.1109/CNSC.2014.6906711
  151. ↑ Simko G., Csermely P., 2013. Nodes Having a Major Influence to Break Cooperation Define a Novel Centrality Measure: Game Centrality. PLoS ONE, 8(6). DOI: 10.1371/journal.pone.0067159
  152. ↑ Sun M.W., Moretti S., Paskov K.M., Stockham N.T., Varma M., Chrisman B.S., Washington P.Y., Jung J.Y., Wall D.P., 2020. Game theoretic centrality: A novel approach to prioritize disease candidate genes by combining biological networks with the Shapley value. BMC Bioinformatics, 21(1). DOI: 10.1186/s12859-020-03693-1
  153. ↑ Liu H., Ma C., Xiang B., Tang M., Zhang H., 2018. Identifying multiple influential spreaders based on generalized closeness centrality. Physica A: Statistical Mechanics and its Applications, 492, pp.2237-2248. DOI: 10.1016/j.physa.2017.11.138
  154. ↑ Agryzkov T., Tortosa L., Vicent J.F., Wilson R., 2019. A centrality measure for urban networks based on the eigenvector centrality concept. Environment and Planning B: Urban Analytics and City Science, 46(4), pp.668-689. DOI: 10.1177/2399808317724444
  155. ↑ Borgatti S., Everett M., 2006. A Graph-theoretic perspective on centrality. Social Networks, 28(4), pp.466-484. DOI: 10.1016/j.socnet.2005.11.005
  156. ↑ Sinclair P., 2009. Network centralization with the Gil Schmidt power centrality index. Social Networks, 31(3), pp.214-219. DOI: 10.1016/j.socnet.2009.04.004
  157. ↑ Chanekar P.V., Nozari E., Cortes J., 2019. Network Modification using a Novel Gramian-based Edge Centrality. Proceedings of the IEEE Conference on Decision and Control, 2019-December, pp.1686-1691. DOI: 10.1109/CDC40024.2019.9028860
  158. ↑ Singh R., Chakraborty A., Manoj B., 2017. GFT centrality: A new node importance measure for complex networks. Physica A: Statistical Mechanics and its Applications, 487, pp.185-195. DOI: 10.1016/j.physa.2017.06.018
  159. ↑ Milenković T., Memišević V., Bonato A., Pržulj N., 2011. Dominating biological networks. PLoS ONE, 6(8). DOI: 10.1371/journal.pone.0023016
  160. ↑ Ma L.L., Ma C., Zhang H.F., Wang B.H., 2016. Identifying influential spreaders in complex networks based on gravity formula. Physica A: Statistical Mechanics and its Applications, 451, pp.205-212. DOI: 10.1016/j.physa.2015.12.162
  161. ↑ Gurfinkel, A.J. and Rikvold, P.A., 2020. A Current-Flow Centrality With Adjustable Reach. arXiv preprint arXiv:2005.14356.
  162. ↑ De Figueiredo B.C.B., Nakamura F.G., Nakamura E.F., 2021. A group-based centrality for undirected multiplex networks: a case study of the Brazilian Car Wash Operation. IEEE Access, . DOI: 10.1109/ACCESS.2021.3086027
  163. ↑ Everett M.G., Borgatti S.P., 1999. The centrality of groups and classes. Journal of Mathematical Sociology, 23(3), pp.181-201. DOI: 10.1080/0022250X.1999.9990219
  164. ↑ Fushimi T., Saito K., Ikeda T., Kazama K., 2019. A new group centrality measure for maximizing the connectedness of network under uncertain connectivity. Studies in Computational Intelligence, 812, pp.3-14. DOI: 10.1007/978-3-030-05411-3_1
  165. ↑ Zhao S., Rousseau R., Ye F., 2011. H-Degree as a basic measure in weighted networks. Journal of Informetrics, 5(4), pp.668-677. DOI: 10.1016/j.joi.2011.06.005
  166. ↑ Zhao S., Rousseau R., Ye F., 2011. H-Degree as a basic measure in weighted networks. Journal of Informetrics, 5(4), pp.668-677. DOI: 10.1016/j.joi.2011.06.005
  167. ↑ Zhao J., Wang P., Lui J.C.S., Towsley D., Guan X., 2017. I/O-efficient calculation of H-group closeness centrality over disk-resident graphs. Information Sciences, 400-401, pp.105-128. DOI: 10.1016/j.ins.2017.03.017
  168. ↑ Li Y., Sheng Y., Ye X., 2020. Group centrality algorithms based on the h-index for identifying influential nodes in large-scale networks. International Journal of Innovative Computing, Information and Control, 16(4), pp.1183-1201. DOI: 10.24507/ijicic.16.04.1183
  169. ↑ Lu P., Dong C., 2019. Ranking the spreading influence of nodes in complex networks based on mixing degree centrality and local structure. International Journal of Modern Physics B, 33(32). DOI: 10.1142/S0217979219503958
  170. ↑ Gao L., Yu S., Li M., Shen Z., Gao Z., 2019. Weighted h-index for identifying influential spreaders. Symmetry, 11(10). DOI: 10.3390/sym11101263
  171. ↑ Hage P., Harary F., 1995. Eccentricity and centrality in networks. Social Networks, 17(1), pp.57-63. DOI: 10.1016/0378-8733(94)00248-9
  172. ↑ Cauteruccio, F., Terracina, G., Ursino, D. and Virgili, L., 2019. Redefining Betweenness Centrality in a Multiple IoT Scenario. In AI&IoT@ AI* IA (pp. 16-27).
  173. ↑ Singh A., Singh R., Iyengar S., 2019. Hybrid centrality measures for service coverage problem. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11917 LNCS, pp.81-94. DOI: 10.1007/978-3-030-34980-6_11
  174. ↑ Marchiori M., Latora V., 2000. Harmony in the small-world. Physica A: Statistical Mechanics and its Applications, 285(3), pp.539-546. DOI: 10.1016/S0378-4371(00)00311-3
  175. ↑ Duron C., 2020. Heatmap centrality: A new measure to identify super-spreader nodes in scale-free networks. PLoS ONE, 15(7 July). DOI: 10.1371/journal.pone.0235690
  176. ↑ Taheri S.M., Mahyar H., Firouzi M., Ghalebi E., Grosu R., Movaghar A., 2017. HellRank: a Hellinger-based centrality measure for bipartite social networks. Social Network Analysis and Mining, 7(1). DOI: 10.1007/s13278-017-0440-7
  177. ↑ Punithavelan, N. and Jaganathan, B., 2017. New web page rank method using HITS Centrality. Global Journal of Pure and Applied Mathematics, 13(10), pp.7229-7235.
  178. ↑ Ma Q., Ma J., 2017. Identifying and ranking influential spreaders in complex networks with consideration of spreading probability. Physica A: Statistical Mechanics and its Applications, 465, pp.312-330. DOI: 10.1016/j.physa.2016.08.041
  179. ↑ Kanwar K., Kaushal S., Kumar H., 2019. A hybrid node ranking technique for finding influential nodes in complex social networks. Library Hi Tech, . DOI: 10.1108/LHT-01-2019-0019
  180. ↑ Stai E., Sotiropoulos K., Karyotis V., Papavassiliou S., 2017. Hyperbolic Embedding for Efficient Computation of Path Centralities and Adaptive Routing in Large-Scale Complex Commodity Networks. IEEE Transactions on Network Science and Engineering, 4(3), pp.140-153. DOI: 10.1109/TNSE.2017.2690258
  181. ↑ Stai E., Sotiropoulos K., Karyotis V., Papavassiliou S., 2016. Hyperbolic Traffic Load Centrality for large-scale complex communications networks. 2016 23rd International Conference on Telecommunications, ICT 2016, . DOI: 10.1109/ICT.2016.7500371
  182. ↑ Kleinberg J.M., 1999. Authoritative sources in a hyperlinked environment. Journal of the ACM, 46(5), pp.604-632. DOI: 10.1145/324133.324140
  183. ↑ Sun H., Liang Y., Chen L., Wang Y., Du W., Shi X., 2013. An improved sum of edge clustering coefficient method for essential protein identification. Journal of Bionanoscience, 7(4), pp.386-390. DOI: 10.1166/jbns.2013.1152
  184. ↑ Sarmento R.P., Cordeiro M., Brazdil P., Gama J., 2018. Efficient incremental laplace centrality algorithm for dynamic networks. Studies in Computational Intelligence, 689, pp.341-352. DOI: 10.1007/978-3-319-72150-7_28
  185. ↑ Ide, K., Namatame, A., Ponnambalam, L., Xiuju, F. and Goh, R.S.M., 2014. A new centrality measure for probabilistic diffusion in network. Advances in Computer Science: An International Journal, 3(5), pp.115-121.
  186. ↑ Cauteruccio, F., Terracina, G., Ursino, D. and Virgili, L., 2019. Redefining Betweenness Centrality in a Multiple IoT Scenario. In AI&IoT@ AI* IA (pp. 16-27).
  187. ↑ Wang Y., Chen B., Li W., Zhang D., 2019. Influential Node Identification in Command and Control Networks Based on Integral k-Shell. Wireless Communications and Mobile Computing, 2019. DOI: 10.1155/2019/6528431
  188. ↑ Salavaty, Abbas and Ramialison, Mirana and Currie, Peter D., IHS; An Integrative Method for the Identification of Network Hubs. Available at SSRN: https://ssrn.com/abstract=3565980 or http://dx.doi.org/10.2139/ssrn.3565980 DOI: 10.2139/ssrn.3565980
  189. ↑ Salavaty, A., Ramialison, M. and Currie, P.D., 2020. Integrated value of influence: an integrative method for the identification of the most influential nodes within networks. Patterns, 1(5), p.100052. DOI: 10.1016/j.patter.2020.100052
  190. ↑ Xu S., Wang P., Lü J., 2017. Iterative Neighbour-Information Gathering for Ranking Nodes in Complex Networks. Scientific Reports, 7. DOI: 10.1038/srep41321
  191. ↑ Borgatti S., Everett M., 2006. A Graph-theoretic perspective on centrality. Social Networks, 28(4), pp.466-484. DOI: 10.1016/j.socnet.2005.11.005
  192. ↑ Seidman S., 1983. Network structure and minimum degree. Social Networks, 5(3), pp.269-287. DOI: 10.1016/0378-8733(83)90028-X
  193. ↑ Niu J., Fan J., Wang L., Stojinenovic M., 2014. K-hop centrality metric for identifying influential spreaders in dynamic large-scale social networks. 2014 IEEE Global Communications Conference, GLOBECOM 2014, , pp.2954-2959. DOI: 10.1109/GLOCOM.2014.7037257
  194. ↑ Alahakoon T., Tripathi R., Kourtellis N., Simha R., Iamnitchi A., 2011. K-path centrality: A new centrality measure in social networks. Proceedings of the 4th Workshop on Social Network Systems, SNS\'11, . DOI: 10.1145/1989656.1989657
  195. ↑ De Meo P., Ferrara E., Fiumara G., Ricciardello A., 2012. A novel measure of edge centrality in social networks. Knowledge-Based Systems, 30, pp.136-150. DOI: 10.1016/j.knosys.2012.01.007
  196. ↑ Jian, X., 2014. KSC centralized index model in complex network. Journal of Networks, 9(5), p.1245.
  197. ↑ Akgün M.K., Tural M.K., 2020. k-step betweenness centrality. Computational and Mathematical Organization Theory, 26(1), pp.55-87. DOI: 10.1007/s10588-019-09301-9
  198. ↑ Akgün M.K., Tural M.K., 2020. k-step betweenness centrality. Computational and Mathematical Organization Theory, 26(1), pp.55-87. DOI: 10.1007/s10588-019-09301-9
  199. ↑ Katz L., 1953. A new status index derived from sociometric analysis. Psychometrika, 18(1), pp.39-43. DOI: 10.1007/BF02289026
  200. ↑ del Rio G., Koschützki D., Coello G., 2009. How to identify essential genes from molecular networks?. BMC Systems Biology, 3, pp.102. DOI: 10.1186/1752-0509-3-102
  201. ↑ Mazalov V., Tsynguev B., 2016. Kirchhoff centrality measure for collaboration network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9795, pp.147-157. DOI: 10.1007/978-3-319-42345-6_13
  202. ↑ Kleinberg, J.M., 1998, January. Authoritative sources in a hyperlinked environment. In Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms (pp. 668-677).
  203. ↑ Shanahan M., Wildie M., 2012. Knotty-centrality: Finding the connective core of a complex network. PLoS ONE, 7(5). DOI: 10.1371/journal.pone.0036579
  204. ↑ Qi X., Fuller E., Wu Q., Wu Y., Zhang C., 2012. Laplacian centrality: A new centrality measure for weighted networks. Information Sciences, 194, pp.240-253. DOI: 10.1016/j.ins.2011.12.027
  205. ↑ Garzon C., Pavas A., 2017. Laplacian eigenvector centrality as tool for assessing causality in power quality. 2017 IEEE Manchester PowerTech, Powertech 2017, . DOI: 10.1109/PTC.2017.7981261
  206. ↑ Jacobsen K., Tien J., 2018. A generalized inverse for graphs with absorption. Linear Algebra and Its Applications, 537, pp.118-147. DOI: 10.1016/j.laa.2017.09.029
  207. ↑ Lü L., Zhang Y., Yeung C., Zhou T., 2011. Leaders in social networks, the delicious case. PLoS ONE, 6(6). DOI: 10.1371/journal.pone.0021202
  208. ↑ Joyce K., Laurienti P., Burdette J., Hayasaka S., 2010. A new measure of centrality for brain networks. PLoS ONE, 5(8). DOI: 10.1371/journal.pone.0012200
  209. ↑ Riquelme F., Gonzalez-Cantergiani P., Molinero X., Serna M., 2018. Centrality measure in social networks based on linear threshold model. Knowledge-Based Systems, 140, pp.92-102. DOI: 10.1016/j.knosys.2017.10.029
  210. ↑ Espejo R., Lumbreras S., Ramos A., Huang T., Bompard E., 2019. An extended metric for the analysis of power-network vulnerability: The line electrical centrality. 2019 IEEE Milan PowerTech, PowerTech 2019, . DOI: 10.1109/PTC.2019.8810514
  211. ↑ Goh K., Kahng B., Kim D., 2001. Universal Behavior of Load Distribution in Scale-Free Networks. Physical Review Letters, 87(27), pp.278701-278701-4. DOI: 10.1103/PhysRevLett.87.278701
  212. ↑ Korn A., Schubert A., Telcs A., 2009. Lobby index in networks. Physica A: Statistical Mechanics and its Applications, 388(11), pp.2221-2226. DOI: 10.1016/j.physa.2009.02.013
  213. ↑ Piraveenan M., Prokopenko M., Zomaya A., 2008. Local assortativeness in scale-free networks. EPL, 84(2). DOI: 10.1209/0295-5075/84/28002
  214. ↑ Li M., Wang J., Chen X., Wang H., Pan Y., 2011. A local average connectivity-based method for identifying essential proteins from the network level. Computational Biology and Chemistry, 35(3), pp.143-150. DOI: 10.1016/j.compbiolchem.2011.04.002
  215. ↑ MacKer J., 2016. An improved local bridging centrality model for distributed network analytics. Proceedings - IEEE Military Communications Conference MILCOM, , pp.600-605. DOI: 10.1109/MILCOM.2016.7795393
  216. ↑ Meghanathan, N., 2017. A computationally lightweight and localized centrality metric in lieu of betweenness centrality for complex network analysis. Vietnam Journal of Computer Science, 4(1), pp.23-38. DOI: 10.1007/s40595-016-0073-1
  217. ↑ XU, G.-Q., MENG, L., TU, D.-Q. & YANG, P.-L. 2021. LCH: a local clustering H-index centrality measure for identifying and ranking influential nodes in complex networks. Chinese Physics B. DOI: 10.1088/1674-1056/abea86
  218. ↑ Li X., Zhou S., Liu J., Lian G., Chen G., Lin C.W., 2019. Communities detection in social network based on local edge centrality. Physica A: Statistical Mechanics and its Applications, 531. DOI: 10.1016/j.physa.2019.121552
  219. ↑ Qi, Y. and Luo, J., 2015. Prediction of essential proteins based on local interaction density. IEEE/ACM transactions on computational biology and bioinformatics, 13(6), pp.1170-1182. DOI: 10.1109/TCBB.2015.2509989
  220. ↑ Han Z., Chen Y., Li M., Liu W., Yang W., 2016. An efficient node influence metric based on triangle in complex networks. Wuli Xuebao/Acta Physica Sinica, 65(16). DOI: 10.7498/aps.65.168901
  221. ↑ Ma X., Ma Y., 2019. The Local Triangle Structure Centrality Method to Rank Nodes in Networks. Complexity, 2019. DOI: 10.1155/2019/9057194
  222. ↑ Cai B., Li X., Gao Y., 2020. An Efficient Trust Inference Algorithm with Local Weighted Centrality for Social Recommendation. IEEE International Conference on Communications, 2020-June. DOI: 10.1109/ICC40277.2020.9149325
  223. ↑ Aleskerov, F.T., Meshcheryakova, N. and Shvydun, S., 2016. Centrality measures in networks based on nodes attributes, long-range interactions and group influence. Long-Range Interactions and Group Influence. DOI: 10.2139/ssrn.3196962
  224. ↑ Ibnoulouafi A., El Haziti M., Cherifi H., 2018. M-Centrality: Identifying key nodes based on global position and local degree variation. Journal of Statistical Mechanics: Theory and Experiment, 2018(7). DOI: 10.1088/1742-5468/aace08
  225. ↑ Kumar R., Manuel S. (2019) A Centrality Measure for Directed Networks: m-Ranking Method. In: Özyer T., Bakshi S., Alhajj R. (eds) Social Networks and Surveillance for Society. Lecture Notes in Social Networks. Springer, Cham. DOI: 10.1007/978-3-319-78256-0_7
  226. ↑ Nie T., Guo Z., Zhao K., Lu Z., 2016. Using mapping entropy to identify node centrality in complex networks. Physica A: Statistical Mechanics and its Applications, 453, pp.290-297. DOI: 10.1016/j.physa.2016.02.009
  227. ↑ White S., Smyth P., 2003. Algorithms for estimating relative importance in networks. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, , pp.266-275. DOI: 10.1145/956750.956782
  228. ↑ Lin C., Chin C., Wu H., Chen S., Ho C., Ko M., 2008. Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology.. Nucleic acids research, 36(Web Server issue). DOI: 10.1093/nar/gkn257
  229. ↑ Pal S., Kundu S., Murthy C., 2014. Centrality measures, upper bound, and influence maximization in large scale directed social networks. Fundamenta Informaticae, 130(3), pp.317-342. DOI: 10.3233/FI-2014-994
  230. ↑ Lin C., Chin C., Wu H., Chen S., Ho C., Ko M., 2008. Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology.. Nucleic acids research, 36(Web Server issue). DOI: 10.1093/nar/gkn257
  231. ↑ Herzog S.M., Hills T.T., 2019. Mediation Centrality in Adversarial Policy Networks. Complexity, 2019. DOI: 10.1155/2019/1918504
  232. ↑ Madotto A., Liu J., 2016. Super-Spreader Identification Using Meta-Centrality. Scientific Reports, 6. DOI: 10.1038/srep38994
  233. ↑ Pontiveros B.B.F., Steichen M., State R., 2019. Mint Centrality: A Centrality Measure for the Bitcoin Transaction Graph. ICBC 2019 - IEEE International Conference on Blockchain and Cryptocurrency, , pp.159-162. DOI: 10.1109/BLOC.2019.8751401
  234. ↑ Wang J., Li C., Xia C., 2018. Improved centrality indicators to characterize the nodal spreading capability in complex networks. Applied Mathematics and Computation, 334, pp.388-400. DOI: 10.1016/j.amc.2018.04.028
  235. ↑ Tsiotas D., Polyzos S., 2015. Introducing a new centrality measure from the transportation network analysis in Greece. Annals of Operations Research, 227(1), pp.93-117. DOI: 10.1007/s10479-013-1434-0
  236. ↑ Masaaki Miyashita and Norihiko Shinomiya. 2015, Modified Betweenness Centrality to Identify Relay Nodes in Data Networks. ACHI 2015 : The Eighth International Conference on Advances in Computer-Human Interactions.
  237. ↑ Wang Y., Wang S., Deng Y., 2019. A modified efficiency centrality to identify influential nodes in weighted networks. Pramana - Journal of Physics, 92(4). DOI: 10.1007/s12043-019-1727-1
  238. ↑ Mazalov V.V., Khitraya V.A., 2021. A Modified Myerson Value for Determining the Centrality of Graph Vertices. Automation and Remote Control, 82(1), pp.145-159. DOI: 10.1134/S0005117921010100
  239. ↑ Magelinski, T., Bartulovic, M. and Carley, K.M., 2020. Modularity-Impact: a Signed Group Centrality Measure for Complex Networks. arXiv preprint arXiv:2003.00056.
  240. ↑ Wang G., Shen Y., Luan E., 2008. Measure of centrality based on modularity matrix. Progress in Natural Science, 18(8), pp.1043-1047. DOI: 10.1016/j.pnsc.2008.03.015
  241. ↑ Fu L., Gao L., Ma X., 2010. A centrality measure based on spectral optimization of modularity density. Science in China, Series F: Information Sciences, 53(9), pp.1727-1737. DOI: 10.1007/s11432-010-4043-4
  242. ↑ Koschützki D., Schwöbbermeyer H., Schreiber F., 2007. Ranking of network elements based on functional substructures. Journal of Theoretical Biology, 248(3), pp.471-479. DOI: 10.1016/j.jtbi.2007.05.038
  243. ↑ Vega-Oliveros D.A., Gomes P.S., E. Milios E., Berton L., 2019. A multi-centrality index for graph-based keyword extraction. Information Processing and Management, 56(6). DOI: 10.1016/j.ipm.2019.102063
  244. ↑ Ivanov S., Gorlushkina N., Ivanova L., 2018. Multi-parametric centrality method for graph network models. AIP Conference Proceedings, 1952. DOI: 10.1063/1.5032005
  245. ↑ Castro N., Stella M., 2019. The multiplex structure of the mental lexicon influences picture naming in people with aphasia. Journal of Complex Networks, 7(6), pp.913-931. DOI: 10.1093/comnet/cnz012
  246. ↑ Donato C., Lo Giudice P., Marretta R., Ursino D., Virgili L., 2019. A well-tailored centrality measure for evaluating patents and their citations. Journal of Documentation, 75(4), pp.750-772. DOI: 10.1108/JD-10-2018-0168
  247. ↑ Berahmand K., Bouyer A., Samadi N., 2018. A new centrality measure based on the negative and positive effects of clustering coefficient for identifying influential spreaders in complex networks. Chaos, Solitons and Fractals, 110, pp.41-54. DOI: 10.1016/j.chaos.2018.03.014
  248. ↑ Wang, Y., Chen, G. 2013, A centrality measure based on two layer neighbors for complex networks. 9: 1 (2013) 25–32.
  249. ↑ Meghanathan, N., 2021. Neighborhood-based bridge node centrality tuple for complex network analysis. Applied Network Science, 6(1), pp.1-36. DOI: 10.1007/s41109-021-00388-1
  250. ↑ Li G., Li M., Wang J., Li Y., Pan Y., 2020. United Neighborhood Closeness Centrality and Orthology for Predicting Essential Proteins. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(4), pp.1451-1458. DOI: 10.1109/TCBB.2018.2889978
  251. ↑ Li G., Li M., Wang J., Li Y., Pan Y., 2020. United Neighborhood Closeness Centrality and Orthology for Predicting Essential Proteins. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(4), pp.1451-1458. DOI: 10.1109/TCBB.2018.2889978
  252. ↑ Maslov S., Sneppen K., 2002. Specificity and stability in topology of protein networks. Science, 296(5569), pp.910-913. DOI: 10.1126/science.1065103
  253. ↑ Kumar S., Panda B.S., 2020. Identifying influential nodes in Social Networks: Neighborhood Coreness based voting approach. Physica A: Statistical Mechanics and its Applications, 553. DOI: 10.1016/j.physa.2020.124215
  254. ↑ Zareie A., Sheikhahmadi A., Jalili M., Fasaei M.S.K., 2020. Finding influential nodes in social networks based on neighborhood correlation coefficient. Knowledge-Based Systems, 194. DOI: 10.1016/j.knosys.2020.105580
  255. ↑ Qiu, L., Zhang, J., Tian, X. and Zhang, S., 2021. Identifying Influential Nodes in Complex Networks Based on Neighborhood Entropy Centrality. The Computer Journal. DOI: 10.1093/comjnl/bxab034
  256. ↑ Tew K.L., Li X.L., Tan S.H., 2007. Functional centrality: detecting lethality of proteins in protein interaction networks.. Genome informatics. International Conference on Genome Informatics, 19, pp.166-177. DOI: 10.1142/9781860949852_0015
  257. ↑ Ruan Y., Lao S., Wang J., Bai L., Chen L., 2017. Node importance measurement based on neighborhood similarity in complex network. Wuli Xuebao/Acta Physica Sinica, 66(3). DOI: 10.7498/aps.66.038902
  258. ↑ Liu W.C., Huang L.C., Liu C.W.J., Jordán F., 2020. A simple approach for quantifying node centrality in signed and directed social networks. Applied Network Science, 5(1). DOI: 10.1007/s41109-020-00288-w
  259. ↑ Wang J., Li M., Wang H., Pan Y., 2012. Identification of essential proteins based on edge clustering coefficient. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(4), pp.1070-1080. DOI: 10.1109/TCBB.2011.147
  260. ↑ Wang P., Lü J., Yu X., 2014. Identification of important nodes in directed biological networks: A network motif approach. PLoS ONE, 9(8). DOI: 10.1371/journal.pone.0106132
  261. ↑ Adebayo I.G., Sun Y., 2020. A novel approach of closeness centrality measure for voltage stability analysis in an electric power grid. International Journal of Emerging Electric Power Systems, 21(3). DOI: 10.1515/ijeeps-2020-0013
  262. ↑ De la Cruz Cabrera O., Matar M., Reichel L., 2021. Centrality measures for node-weighted networks via line graphs and the matrix exponential. Numerical Algorithms, . DOI: 10.1007/s11075-020-01050-0
  263. ↑ Lyu T., Sun F., Zhang Y., 2020. Node Conductance: A Scalable Node Centrality Measure on Big Networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12085 LNAI, pp.529-541. DOI: 10.1007/978-3-030-47436-2_40
  264. ↑ Martin T., Zhang X., Newman M.E.J., 2014. Localization and centrality in networks. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 90(5). DOI: 10.1103/PhysRevE.90.052808
  265. ↑ Arrigo F., Grindrod P., Higham D., Noferini V., 2018. Non-backtracking walk centrality for directed networks. Journal of Complex Networks, 6(1), pp.54-78. DOI: 10.1093/comnet/cnx025
  266. ↑ Wang Z., Dueñas-Osorio L., Padgett J., 2015. A new mutually reinforcing network node and link ranking algorithm. Scientific Reports, 5. DOI: 10.1038/srep15141
  267. ↑ Ghosh R., Lerman K., 2011. Parameterized centrality metric for network analysis. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 83(6). DOI: 10.1103/PhysRevE.83.066118
  268. ↑ Reiffers-Masson A., Labatut V., 2017. Opinion-based centrality in multiplex networks: A convex optimization approach. Network Science, 5(2), pp.213-234. DOI: 10.1017/nws.2017.7
  269. ↑ Ghalmane Z., Cherifi C., Cherifi H., Hassouni M.E., 2019. Centrality in Complex Networks with Overlapping Community Structure. Scientific Reports, 9(1). DOI: 10.1038/s41598-019-46507-y
  270. ↑ Andrade R., Rêgo L., 2019. p-means centrality. Communications in Nonlinear Science and Numerical Simulation, 68, pp.41-55. DOI: 10.1016/j.cnsns.2018.08.002
  271. ↑ Potapov A., Goemann B., Wingender E., 2008. The pairwise disconnectivity index as a new metric for the topological analysis of regulatory networks. BMC Bioinformatics, 9. DOI: 10.1186/1471-2105-9-227
  272. ↑ Lee K.H., Kim M.H., 2020. Linearization of dependency and sampling for participation-based betweenness centrality in very large b-hypergraphs. ACM Transactions on Knowledge Discovery from Data, 14(3). DOI: 10.1145/3375399
  273. ↑ Senturk I.F., 2019. Partition-aware centrality measures for connectivity restoration in mobile sensor networks. International Journal of Sensor Networks, 30(1), pp.1-12. DOI: 10.1504/IJSNET.2019.099218
  274. ↑ Senturk I.F., 2019. Partition-aware centrality measures for connectivity restoration in mobile sensor networks. International Journal of Sensor Networks, 30(1), pp.1-12. DOI: 10.1504/IJSNET.2019.099218
  275. ↑ Senturk I.F., 2019. Partition-aware centrality measures for connectivity restoration in mobile sensor networks. International Journal of Sensor Networks, 30(1), pp.1-12. DOI: 10.1504/IJSNET.2019.099218
  276. ↑ Syarif A., Abouaissa A., Idoumghar L., Lorenz P., Schott R., Staples G., 2019. New path centrality based on operator calculus approach for wireless sensor network deployment. IEEE Transactions on Emerging Topics in Computing, 7(1), pp.162-173. DOI: 10.1109/TETC.2016.2585045
  277. ↑ Coutinho R., Boukerche A., Vieira L., Loureiro A., 2016. A novel centrality metric for topology control in underwater sensor networks. MSWiM 2016 - Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, , pp.205-212. DOI: 10.1145/2988287.2989162
  278. ↑ Li M., Zhang H., Wang J., Pan Y., 2012. A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data. BMC Systems Biology, 6. DOI: 10.1186/1752-0509-6-15
  279. ↑ Piraveenan M., Prokopenko M., Hossain L., 2013. Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks. PLoS ONE, 8(1). DOI: 10.1371/journal.pone.0053095
  280. ↑ Nathan E., Zakrzewska A., Riedy J., Bader D., 2017. Local community detection in dynamic graphs using personalized centrality. Algorithms, 10(3). DOI: 10.3390/a10030102
  281. ↑ Nathan E., Zakrzewska A., Riedy J., Bader D., 2017. Local community detection in dynamic graphs using personalized centrality. Algorithms, 10(3). DOI: 10.3390/a10030102
  282. ↑ Szalay K., Csermely P., 2013. Perturbation Centrality and Turbine: A Novel Centrality Measure Obtained Using a Versatile Network Dynamics Tool. PLoS ONE, 8(10). DOI: 10.1371/journal.pone.0078059
  283. ↑ Kwon H., Choi Y.H., Lee J.M., 2019. A Physarum Centrality Measure of the Human Brain Network. Scientific Reports, 9(1). DOI: 10.1038/s41598-019-42322-7
  284. ↑ Aleskerov F., Roman A., Rezyapova A., Yakuba V., 2020. New Centrality Measures in Networks and their Applications to the International Trade and Migration Networks. Proceedings - IEEE Computer Society\'s Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS, 2020-November. DOI: 10.1109/MASCOTS50786.2020.9285957
  285. ↑ Everett M., Borgatti S., 2014. Networks containing negative ties. Social Networks, 38(1), pp.111-120. DOI: 10.1016/j.socnet.2014.03.005
  286. ↑ Smith J., Halgin D., Kidwell-Lopez V., Labianca G., Brass D., Borgatti S., 2014. Power in politically charged networks. Social Networks, 36(1), pp.162-176. DOI: 10.1016/j.socnet.2013.04.007
  287. ↑ Khan J.A., Westphal C., Ghamri-Doudane Y., 2018. A Popularity-aware Centrality Metric for Content Placement in Information Centric Networks. 2018 International Conference on Computing, Networking and Communications, ICNC 2018, , pp.554-560. DOI: 10.1109/ICCNC.2018.8390396
  288. ↑ De Meo P., Levene M., Provetti A., 2019. Potential gain as a centrality measure. Proceedings - 2019 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2019, , pp.418-422. DOI: 10.1145/3350546.3352559
  289. ↑ Hellervik A., Nilsson L., Andersson C., 2019. Preferential centrality – A new measure unifying urban activity, attraction and accessibility. Environment and Planning B: Urban Analytics and City Science, 46(7), pp.1331-1346. DOI: 10.1177/2399808318812888
  290. ↑ Ilyas M., Radha H., 2010. A KLT-inspired node centrality for identifying influential neighborhoods in graphs. 2010 44th Annual Conference on Information Sciences and Systems, CISS 2010, . DOI: 10.1109/CISS.2010.5464971
  291. ↑ Alshahrani M., Fuxi Z., Sameh A., Mekouar S., Huang S., 2018. Top-K influential users selection based on combined Katz centrality and propagation probability. 2018 3rd IEEE International Conference on Cloud Computing and Big Data Analysis, ICCCBDA 2018, , pp.52-56. DOI: 10.1109/ICCCBDA.2018.8386486
  292. ↑ Chua H., Bhowmick S., Tucker-Kellogg L., Zhao Q., Dewey C., Yu H., 2011. PANI: A novel algorithm for fast discovery of Putative TArget Nodes in signaling networks. 2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, BCB 2011, , pp.284-288. DOI: 10.1145/2147805.2147836
  293. ↑ Izaac J.A., Wang J.B., Abbott P.C., Ma X.S., 2017. Quantum centrality testing on directed graphs via PT-symmetric quantum walks. Physical Review A, 96(3). DOI: 10.1103/PhysRevA.96.032305
  294. ↑ Boito, P. and Grena, R., 2021. Quantum hub and authority centrality measures for directed networks based on continuous-time quantum walks. arXiv preprint arXiv:2104.09637.
  295. ↑ Ma Y., Cao Z., Qi X., 2019. Quasi-Laplacian centrality: A new vertex centrality measurement based on Quasi-Laplacian energy of networks. Physica A: Statistical Mechanics and its Applications, 527. DOI: 10.1016/j.physa.2019.121130
  296. ↑ Avrachenkov K., Borkar V., Nemirovsky D., 2010. Quasi-stationary distributions as centrality measures for the giant strongly connected component of a reducible graph. Journal of Computational and Applied Mathematics, 234(11), pp.3075-3090. DOI: 10.1016/j.cam.2010.02.001
  297. ↑ Plana F., Perez J., 2019. QuickCent: A Fast and Frugal Heuristic for Centrality Estimation on Networks. Proceedings - 2018 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018, (), pp.238-245. DOI: 10.1109/WI.2018.00-84
  298. ↑ Lee T., Lee H., Hwang K., 2013. Identifying superspreaders for epidemics using R0-adjusted network centrality. Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, , pp.2239-2249. DOI: 10.1109/WSC.2013.6721600
  299. ↑ Valente T., Foreman R., 1998. Integration and radiality: Measuring the extent of an individual\'s connectedness and reachability in a network. Social Networks, 20(1), pp.89-105. DOI: 10.1016/S0378-8733(97)00007-5
  300. ↑ Borgatti S., Everett M., 2006. A Graph-theoretic perspective on centrality. Social Networks, 28(4), pp.466-484. DOI: 10.1016/j.socnet.2005.11.005
  301. ↑ Noh J., Rieger H., 2004. Random Walks on Complex Networks. Physical Review Letters, 92(11). DOI: 10.1103/PhysRevLett.92.118701
  302. ↑ Ranjan, G. and Zhang, Z.L., 2010. On random eccentricity in complex networks. Tech. Report.
  303. ↑ Dai Z., Li P., Chen Y., Zhang K., Zhang J., 2019. Influential node ranking via randomized spanning trees. Physica A: Statistical Mechanics and its Applications, 526. DOI: 10.1016/j.physa.2019.02.047
  304. ↑ Dai Z., Li P., Chen Y., Zhang K., Zhang J., 2019. Influential node ranking via randomized spanning trees. Physica A: Statistical Mechanics and its Applications, 526. DOI: 10.1016/j.physa.2019.02.047
  305. ↑ Noh J., Rieger H., 2004. Random Walks on Complex Networks. Physical Review Letters, 92(11). DOI: 10.1103/PhysRevLett.92.118701
  306. ↑ Wąs, T., Rahwan, T. and Skibski, O., 2019, July. Random Walk Decay Centrality. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, No. 01, pp. 2197-2204). DOI: 10.1609/aaai.v33i01.33012197
  307. ↑ Ercsey-Ravasz M., Lichtenwalter R.N., Chawla N.V., Toroczkai Z., 2012. Range-limited centrality measures in complex networks. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 85(6). DOI: 10.1103/PhysRevE.85.066103
  308. ↑ Negahban S., Oh S., Shah D., 2017. Rank centrality: Ranking from pairwise comparisons. Operations Research, 65(1), pp.266-287. DOI: 10.1287/opre.2016.1534
  309. ↑ Agryzkov T., Oliver J., Tortosa L., Vicent J., 2014. A new betweenness centrality measure based on an algorithm for ranking the nodes of a network. Applied Mathematics and Computation, 244, pp.467-478. DOI: 10.1016/j.amc.2014.07.026
  310. ↑ Qiao T., Shan W., Zhou C., 2017. How to identify the most powerful node in complex networks? A novel entropy centrality approach. Entropy, 19(11). DOI: 10.3390/e19110614
  311. ↑ Donato C., Lo Giudice P., Marretta R., Ursino D., Virgili L., 2019. A well-tailored centrality measure for evaluating patents and their citations. Journal of Documentation, 75(4), pp.750-772. DOI: 10.1108/JD-10-2018-0168
  312. ↑ Sotoodeh H., Falahrad M., 2019. Relative Degree Structural Hole Centrality, C<inf>RD−SH</inf>: A New Centrality Measure in Complex Networks. Journal of Systems Science and Complexity, 32(5), pp.1306-1323. DOI: 10.1007/s11424-018-7331-5
  313. ↑ Vukičević, D., Škrekovski, R. and Tepeh, A., 2016. Relative edge betweenness centrality. Ars Mathematica Contemporanea, 12(2), pp.261-270. DOI: 10.26493/1855-3974.863.169
  314. ↑ Giustolisi O., Ridolfi L., Simone A., 2020. Embedding the intrinsic relevance of vertices in network analysis: the case of centrality metrics. Scientific Reports, 10(1). DOI: 10.1038/s41598-020-60151-x
  315. ↑ Dangalchev C., 2006. Residual closeness in networks. Physica A: Statistical Mechanics and its Applications, 365(2), pp.556-564. DOI: 10.1016/j.physa.2005.12.020
  316. ↑ Del Sol A., Fujihashi H., Amoros D., Nussinov R., 2006. Residues crucial for maintaining short paths in network communication mediate signaling in proteins. Molecular Systems Biology, 2. DOI: 10.1038/msb4100063
  317. ↑ Zhang, Y., Shao, C., He, S. and Gao, J., 2020. Resilience centrality in complex networks. Physical Review E, 101(2), p.022304. DOI: 10.1103/PhysRevE.101.022304
  318. ↑ Shah, D. and Zaman, T., 2010, June. Detecting sources of computer viruses in networks: theory and experiment. In Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems (pp. 203-214). DOI: 10.1145/1811039.1811063
  319. ↑ Lempel R., Moran S., 2002. SALSA: The stochastic approach for link-structure analysis. ACM Transactions on Information Systems, 19(2), pp.131-160. DOI: 10.1145/382979.383041
  320. ↑ Kermarrec A.M., Le Merrer E., Sericola B., Trédan G., 2011. Second order centrality: Distributed assessment of nodes criticity in complex networks. Computer Communications, 34(5), pp.619-628. DOI: 10.1016/j.comcom.2010.06.007
  321. ↑ Chen D., Lü L., Shang M., Zhang Y., Zhou T., 2012. Identifying influential nodes in complex networks. Physica A: Statistical Mechanics and its Applications, 391(4), pp.1777-1787. DOI: 10.1016/j.physa.2011.09.017
  322. ↑ Huang, S., Cui, H. and Ding, Y., 2014. Evaluation of node importance in complex networks. arXiv preprint arXiv:1402.5743.
  323. ↑ Aleskerov F., Andrievskaya I., Permjakova E., 2016. Key borrowers detected by the intensities of their short-range interactions. Springer Proceedings in Mathematics and Statistics, 156, pp.267-280. DOI: 10.1007/978-3-319-29608-1_18
  324. ↑ Zhou X., Liang X., Zhao J., Zhang S., 2018. Cycle Based Network Centrality. Scientific Reports, 8(1). DOI: 10.1038/s41598-018-30249-4
  325. ↑ Xu Y., Feng Z., Qi X., 2021. Signless-laplacian eigenvector centrality: A novel vital nodes identification method for complex networks. Pattern Recognition Letters, 148, pp.7-14. DOI: 10.1016/j.patrec.2021.04.018
  326. ↑ Wang D., Zou X., 2018. A new centrality measure of nodes in multilayer networks under the framework of tensor computation. Applied Mathematical Modelling, 54, pp.46-63. DOI: 10.1016/j.apm.2017.07.012
  327. ↑ Agha Mohammad Ali Kermani M., Badiee A., Aliahmadi A., Ghazanfari M., Kalantari H., 2016. Introducing a procedure for developing a novel centrality measure (Sociability Centrality) for social networks using TOPSIS method and genetic algorithm. Computers in Human Behavior, 56, pp.295-305. DOI: 10.1016/j.chb.2015.11.008
  328. ↑ Li B., Gao Z., Shan X., Zhou W., Ferrara E., 2019. Sorec: A social-relation based centrality measure in mobile social networks. 2019 26th International Conference on Telecommunications, ICT 2019, , pp.485-489. DOI: 10.1109/ICT.2019.8798844
  329. ↑ Cauteruccio, F., Terracina, G., Ursino, D. and Virgili, L., 2019. Redefining Betweenness Centrality in a Multiple IoT Scenario. In AI&IoT@ AI* IA (pp. 16-27).
  330. ↑ Naderi Yeganeh P., Naderi Yeganeh P., Richardson C., Saule E., Loraine A., Taghi Mostafavi M., 2020. Revisiting the use of graph centrality models in biological pathway analysis. BioData Mining, 13(1). DOI: 10.1186/s13040-020-00214-x
  331. ↑ Qi X., Fuller E., Luo R., Zhang C.Q., 2015. A novel centrality method for weighted networks based on the Kirchhoff polynomial. Pattern Recognition Letters, 58, pp.51-60. DOI: 10.1016/j.patrec.2015.02.007
  332. ↑ Liu A., Porter M.A., 2020. Spatial strength centrality and the effect of spatial embeddings on network architecture. Physical Review E, 101(6). DOI: 10.1103/PhysRevE.101.062305
  333. ↑ Hamilton K., Mintz T., Date P., Schuman C.D., 2020. Spike-based graph centrality measures. ACM International Conference Proceeding Series, . DOI: 10.1145/3407197.3407199
  334. ↑ Oggier F., Phetsouvanh S., Datta A., 2019. A split-and-transfer flow based entropic centrality. PeerJ Computer Science, 2019(9). DOI: 10.7717/peerj-cs.220
  335. ↑ Chen X., Tan M., Zhao J., Yang T., Wu D., Zhao R., 2019. Identifying influential nodes in complex networks based on a spreading influence related centrality. Physica A: Statistical Mechanics and its Applications, 536. DOI: 10.1016/j.physa.2019.122481
  336. ↑ Vogiatzis, C. and Camur, M.C., 2019. Identification of essential proteins using induced stars in protein–protein interaction networks. INFORMS Journal on Computing, 31(4), pp.703-718. DOI: 10.1287/ijoc.2018.0872
  337. ↑ Bonacich P., Lloyd P., 2004. Calculating status with negative relations. Social Networks, 26(4), pp.331-338. DOI: 10.1016/j.socnet.2004.08.007
  338. ↑ Barrat A., Barthélemy M., Pastor-Satorras R., Vespignani A., 2004. The architecture of complex weighted networks. Proceedings of the National Academy of Sciences of the United States of America, 101(11), pp.3747-3752. DOI: 10.1073/pnas.0400087101
  339. ↑ Brandes, U., 2005. Network analysis: methodological foundations (Vol. 3418). Springer Science & Business Media.
  340. ↑ Ghaffar F., Hurley N., 2020. Structural hole centrality: evaluating social capital through strategic network formation. Computational Social Networks, 7(1). DOI: 10.1186/s40649-020-00079-4
  341. ↑ Wang P., Yu X., Lü J., 2014. Identification and evolution of structurally dominant nodes in protein-protein interaction networks. IEEE Transactions on Biomedical Circuits and Systems, 8(1), pp.87-97. DOI: 10.1109/TBCAS.2014.2303160
  342. ↑ Estrada E., Rodríguez-Velázquez J.A., 2005. Subgraph centrality in complex networks. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 71(5). DOI: 10.1103/PhysRevE.71.056103
  343. ↑ Wang H., Li M., Wang J., Pan Y., 2011. A new method for identifying essential proteins based on edge clustering coefficient. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6674 LNBI, pp.87-98. DOI: 10.1007/978-3-642-21260-4_12
  344. ↑ Saito K., Kimura M., Ohara K., Motoda H., 2016. Super mediator - A new centrality measure of node importance for information diffusion over social network. Information Sciences, 329, pp.985-1000. DOI: 10.1016/j.ins.2015.03.034
  345. ↑ Britt B.C., Hayes J.L., Musaev A., Sheinidashtegol P., Parrott S., Albright D.L., 2021. Using targeted betweenness centrality to identify bridges to neglected users in the Twitter conversation on veteran suicide. Social Network Analysis and Mining, 11(1). DOI: 10.1007/s13278-021-00747-x
  346. ↑ Saito, K., Fushimi, T., Ohara, K., Kimura, M. and Motoda, H., Efficient computation of target-oriented link criticalness centrality in uncertain graphs.
  347. ↑ Shao H., Mesbahi M., Li D., Xi Y., 2017. Inferring centrality from network snapshots. Scientific Reports, 7. DOI: 10.1038/srep40642
  348. ↑ Huang D., Yu Z., 2017. Dynamic-Sensitive centrality of nodes in temporal networks. Scientific Reports, 7. DOI: 10.1038/srep41454
  349. ↑ Béres F., Pálovics R., Oláh A., Benczúr A.A., 2018. Temporal walk based centrality metric for graph streams. Applied Network Science, 3(1). DOI: 10.1007/s41109-018-0080-5
  350. ↑ Zhang W., Xu J., Li Y., Zou X., 2018. Detecting Essential Proteins Based on Network Topology, Gene Expression Data, and Gene Ontology Information. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(1), pp.109-116. DOI: 10.1109/TCBB.2016.2615931
  351. ↑ Stelzl U., Worm U., Lalowski M., Haenig C., Brembeck F.H., Goehler H., Stroedicke M., Zenkner M., Schoenherr A., Koeppen S., Timm J., Mintzlaff S., Abraham C., Bock N., Kietzmann S., Goedde A., Toksöz E., Droege A., Krobitsch S., Korn B., Birchmeier W., Lehrach H., Wanker E.E., 2005. A human protein-protein interaction network: A resource for annotating the proteome. Cell, 122(6), pp.957-968. DOI: 10.1016/j.cell.2005.08.029
  352. ↑ Ding C., Li K., 2018. Centrality ranking in multiplex networks using topologically biased random walks. Neurocomputing, 312, pp.263-275. DOI: 10.1016/j.neucom.2018.05.109
  353. ↑ Lv L., Zhang K., Bardou D., Zhang T., Cai Y., 2019. A new centrality measure based on topologically biased random walks for multilayer networks. Journal of the Physical Society of Japan, 88(2). DOI: 10.7566/JPSJ.88.024010
  354. ↑ Liu W.C., Huang L.C., Liu C.W.J., Jordán F., 2020. A simple approach for quantifying node centrality in signed and directed social networks. Applied Network Science, 5(1). DOI: 10.1007/s41109-020-00288-w
  355. ↑ Amshi, A.T. and Shu, J., 2020. Complex Network Influence Evaluation based on extension of Grueblers Equation. arXiv preprint arXiv:2012.13617. DOI: 10.13140/RG.2.2.14025.36960
  356. ↑ Stai E., Sotiropoulos K., Karyotis V., Papavassiliou S., 2016. Hyperbolic Traffic Load Centrality for large-scale complex communications networks. 2016 23rd International Conference on Telecommunications, ICT 2016, . DOI: 10.1109/ICT.2016.7500371
  357. ↑ Zhang Q., Karsai M., Vespignani A., 2018. Link transmission centrality in large-scale social networks. EPJ Data Science, 7(1). DOI: 10.1140/epjds/s13688-018-0162-8
  358. ↑ Zaoli S., Mazzarisi P., Lillo F., 2019. Trip Centrality: walking on a temporal multiplex with non-instantaneous link travel time. Scientific Reports, 9(1). DOI: 10.1038/s41598-019-47115-6
  359. ↑ Avrachenkov K., Litvak N., Medyanikov V., Sokol M., 2013. Alpha current flow betweenness centrality. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8305 LNCS, pp.106-117. DOI: 10.1007/978-3-319-03536-9_9
  360. ↑ Zhang B., Zhang L., Mu C., Zhao Q., Song Q., Hong X., 2019. A most influential node group discovery method for influence maximization in social networks: A trust-based perspective. Data and Knowledge Engineering, 121, pp.71-87. DOI: 10.1016/j.datak.2019.05.001
  361. ↑ Richters O., Peixoto T., 2011. Trust transitivity in social networks. PLoS ONE, 6(4). DOI: 10.1371/journal.pone.0018384
  362. ↑ Cerdeira, J.O. and Silva, P.C., 2021. A centrality notion for graphs based on Tukey depth. Applied Mathematics and Computation, 409, p.126409. DOI: 10.1016/j.amc.2021.126409
  363. ↑ Pu C., Cui W., Yang J., 2014. Tunable path centrality: Quantifying the importance of paths in networks. Physica A: Statistical Mechanics and its Applications, 405, pp.267-277. DOI: 10.1016/j.physa.2014.03.039
  364. ↑ Weng J., Lim E.P., Jiang J., He Q., 2010. TwitterRank: Finding topic-sensitive influential twitterers. WSDM 2010 - Proceedings of the 3rd ACM International Conference on Web Search and Data Mining, , pp.261-270. DOI: 10.1145/1718487.1718520
  365. ↑ Pedroche F., Romance M., Criado R., 2016. A biplex approach to PageRank centrality: From classic to multiplex networks. Chaos, 26(6). DOI: 10.1063/1.4952955
  366. ↑ Li, M., Lu, Y., Niu, Z. and Wu, F.X., 2017. United Complex Centrality for Identification of Essential Proteins from PPI Networks. IEEE/ACM transactions on computational biology and bioinformatics, 14(2), pp.370-380. DOI: 10.1109/TCBB.2015.2394487
  367. ↑ Li, M., Lu, Y., Niu, Z. and Wu, F.X., 2017. United Complex Centrality for Identification of Essential Proteins from PPI Networks. IEEE/ACM transactions on computational biology and bioinformatics, 14(2), pp.370-380. DOI: 10.1109/TCBB.2015.2394487
  368. ↑ De Domenico M., Solé-Ribalta A., Omodei E., Gómez S., Arenas A., 2015. Ranking in interconnected multilayer networks reveals versatile nodes. Nature Communications, 6. DOI: 10.1038/ncomms7868
  369. ↑ Rossi L., Torsello A., 2017. Measuring vertex centrality using the Holevo quantity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10310 LNCS, pp.154-164. DOI: 10.1007/978-3-319-58961-9_14
  370. ↑ Estrada E., Hatano N., 2010. A vibrational approach to node centrality and vulnerability in complex networks. Physica A: Statistical Mechanics and its Applications, 389(17), pp.3648-3660. DOI: 10.1016/j.physa.2010.03.030
  371. ↑ Iannelli F., Mariani M., Sokolov I., 2018. Influencers identification in complex networks through reaction-diffusion dynamics. Physical Review E, 98(6). DOI: 10.1103/PhysRevE.98.062302
  372. ↑ Zhang J., Chen D., Dong Q., Zhao Z., 2016. Identifying a set of influential spreaders in complex networks. Scientific Reports, 6. DOI: 10.1038/srep27823
  373. ↑ Zhao S., Rousseau R., Ye F., 2011. H-Degree as a basic measure in weighted networks. Journal of Informetrics, 5(4), pp.668-677. DOI: 10.1016/j.joi.2011.06.005
  374. ↑ Youm Y., Lee B., Kim J., 2021. A measure of centrality in cyclic diffusion processes: Walk-betweenness. PLoS ONE, 16(1 January). DOI: 10.1371/journal.pone.0245476
  375. ↑ Ghalmane Z., Hassouni M.E., Cherifi H., 2018. Betweenness Centrality for Networks with Non-Overlapping Community Structure. 2018 IEEE Workshop on Complexity in Engineering, COMPENG 2018, . DOI: 10.1109/CompEng.2018.8536229
  376. ↑ Tang X., Wang J., Zhong J., Pan Y., 2014. Predicting essential proteins basedon weighted degree centrality. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(2), pp.407-418. DOI: 10.1109/TCBB.2013.2295318
  377. ↑ Gao L., Yu S., Li M., Shen Z., Gao Z., 2019. Weighted h-index for identifying influential spreaders. Symmetry, 11(10). DOI: 10.3390/sym11101263
  378. ↑ Li Q., Zhou T., Lü L., Chen D., 2014. Identifying influential spreaders by weighted LeaderRank. Physica A: Statistical Mechanics and its Applications, 404, pp.47-55. DOI: 10.1016/j.physa.2014.02.041
  379. ↑ Karabekmez M., Kirdar B., 2016. A novel topological centrality measure capturing biologically important proteins. Molecular BioSystems, 12(2), pp.666-673. DOI: 10.1039/C5MB00732A
  380. ↑ Wang J., Hou X., Li K., Ding Y., 2017. A novel weight neighborhood centrality algorithm for identifying influential spreaders in complex networks. Physica A: Statistical Mechanics and its Applications, 475, pp.88-105. DOI: 10.1016/j.physa.2017.02.007
  381. ↑ Sun H.l., Chen D.b., He J.l., Ch\'ng E., 2019. A voting approach to uncover multiple influential spreaders on weighted networks. Physica A: Statistical Mechanics and its Applications, 519, pp.303-312. DOI: 10.1016/j.physa.2018.12.001
  382. ↑ Torres, L., Chan, K.S., Tong, H. and Eliassi-Rad, T., 2021. Nonbacktracking Eigenvalues under Node Removal: X-Centrality and Targeted Immunization. SIAM Journal on Mathematics of Data Science, 3(2), pp.656-675. DOI: 10.1137/20M1352132
  383. ↑ Torres, L., Chan, K.S., Tong, H. and Eliassi-Rad, T., 2021. Nonbacktracking Eigenvalues under Node Removal: X-Centrality and Targeted Immunization. SIAM Journal on Mathematics of Data Science, 3(2), pp.656-675. DOI: 10.1137/20M1352132
  384. ↑ Li H., Zhang Z., 2018. Kirchhoff index as a measure of edge centrality in weighted networks: Nearly linear time algorithms. Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms, , pp.2377-2396. DOI: 10.1137/1.9781611975031.153
  385. ↑ Criado R., Flores J., García E., del Amo A.J.G., Pérez Á., Romance M., 2019. On the Failed to parse (syntax error): {\displaystyle <mi is="true">α</mi>} -nonbacktracking centrality for complex networks: Existence and limit cases. Journal of Computational and Applied Mathematics, 350, pp.35-45. DOI: 10.1016/j.cam.2018.09.048
  386. ↑ De Medeiros D.S.V., Campista M.E.M., Mitton N., De Amorim M.D., Pujolle G., 2017. The Power of Quasi-Shortest Paths: ρ-Geodesic Betweenness Centrality. IEEE Transactions on Network Science and Engineering, 4(3), pp.187-200. DOI: 10.1109/TNSE.2017.2708705


This article "Centrality Measures" is from Wikipedia. The list of its authors can be seen in its historical and/or the page Edithistory:Centrality Measures. Articles copied from Draft Namespace on Wikipedia could be seen on the Draft Namespace of Wikipedia and not main one.


Retrieved from "https://en.everybodywiki.com/index.php?title=Centrality_Measures&oldid=5283624"
License CC BY-SA 3.0
Powered by MediaWiki