Ethical Data Collection With Social Networking Services

Data collection is the procedure of collecting and analysing information on specific material in an established framework, which then allows an individual to answer applicable questions and appraise results. Data collection is an attribute of exploration in all sectors of study. While methods differ by field, the prominence on ensuring reliable and truthful collection remains the same. The objective for all data collection is to apprehend credible information that enables examination to guide to the formation of persuasive and reliable answers to the questions that have been presented.

Regardless of the area of research for interpreting data (quantitative or qualitative), correct data gathering is necessary to sustain the integrity of research. The option of appropriate data assemblage instruments (existing, modified, or newly developed) and clearly delineated instructions for their accurate use decline the likelihood of errors. A formal data collection process is necessary as it ensures that the data gathered are both defined and accurate. This way, subsequent decisions based on arguments embodied in the findings are made using valid data. The process provides both a baseline from which to measure and in certain cases an indication of what to improve.

There are 5 common data collection methods:

• Closed-ended surveys
• Open-ended surveys and questionnaires
• 1-on-1 interviews
• Focus groups
• Direct observation

Data Collection Methods

In today's society, there is immense confusion from the general public on how their personal data is being collected. Data collection methods are extremely technical and the consumers opt into online services, which harness consumer data and utilise it for advertising promotions. Currently, there are several ways for third party vendors to gather consumer data. Flickr is an example of a social media platform that enables geotagged photos that allows consumers to observe the exact location of where an individual is visiting or staying. Geotagged photos make it easy for third party vendors to see where an individual is located or traveling to. There is also an increase use of phishing, which reveals volatile information through mysterious links and downloads through email, messages, and other communications. Social media has opened up an entirely new realm for hackers to get information from normal posts and messages.

Search Engines

The letters of "Google" are each purely colored (from left to right) with blue, red, yellow, blue, green, and red in Product Sans font. The e is slightly angled.

Search engines are a direct way to find key data without scanning every site on the internet. Keyword generation will guide users to the search engine results page. So it is necessary to make sure that the keywords typed are precise and correct. There are many such search engines, some of which may lead the user to fake sites which may obtain personal information or are laden with viruses. Google's search engine uses a machine learning method titled a crawler. A crawler is the discovery process in which search engines send out a team of robots (known as crawlers or spiders) to find new and updated content. Content can vary — it could be a webpage, an image, a video, a PDF, etc. — but regardless of the format, content is discovered by links. The more related keywords and hyperlinks on a web page the more likely Google's crawler will find a companies website. Further, Bing's search engine algorithm is a simplified version of Google. Bing uses exact keyword generation to rank websites on their search engine result pages. Meaning the more exact keywords users type in the search bar in comparison with a website on the internet. The higher correlation of similar keywords the higher the companies website ranks on Bing.

Location Data

English Point-to-point wireless link for Internet connectivity with FreedomBox

On the majority of social media platforms, user's geographical location can be collected by users (through opting into check-in applications like Instagram and Facebook Places) or by web applications (through technologies like IP address geolocation, cellphone network triangulation, RFID and GPS). The method used matters less than the outcome, which holds that the information generated is coupled with the geographical location where the consumer created it. Furthermore, many web applications partner the contents of other forms of data like OS language, device type and capture time. The outcome is that by posting, tweeting or taking pictures, users produce and share an enormous amount of personal information within their online profiles. Beacon technology are hardware transmitters - a class of bluetooth low energy (LE) devices that broadcast their identifier to nearby portable electronic devices. The technology enables smartphones, tablets and other devices to perform actions when in close proximity to a beacon.

Fundamentals of Data Ethics

Data ethics is concerned with the following principles:

1. Ownership - consumers own their own data.
2. Transaction transparency - If consumers personal information is utilised, they should have translucent access to the algorithm framework used to create aggregate data sets.
3. Consent - If a consumer would like to have personal information, one needs informed and directly expressed permission of what personal information moves to whom, when, and for what purpose from the owner of the data.
4. Privacy - If data negotiations occur all efforts must be made to maintain privacy.
5. Currency - consumers should be aware of financial transactions resulting from the use of their personal data and the scale of these transactions.
6. Openness - Aggregate data sets should be freely accessible

Ownership

Personal information refers to data packs profiling consumers fluctuating from physical attributes to their preferences and behaviour. Examples of personal data include: Genome data, GPS location, written communication, spoken communication, lists of contacts, internet browsing habits, and financial transactions. A digital identity comprises all personal information mirroring, representing and linked to our physical and psychological self. The differentiation between information sectors is not always clear and concise. For example, health data and banking data are connected due to behaviour and lifestyle can be inferred through banking data and is hugely valuable for predicting risk of chronic disease. Thus, banking data is also health data. Health data can indicate how much an individual spends on healthcare, therefore health data is also banking data. These overlaps exist in between other data categories too, for example, location data, Internet browsing data, tax data are essentially all about individuals.

This work, hereby publish it under the following license: English Memorandum proposing Data Embassy Principles to enforce EU data protection obligations

European laws, the General Data Protection Regulation, indicate that individuals own their own personal data

Transaction transparency

Apprehension has been raised around how personal biases can be consolidated into algorithm outlines resulting in systematic subjection. The algorithm outline should be translucently disclosed. Adequate efforts should be pressed to take into account the dissimilarities between individuals and groups, without losing the notion of equality. Algorithm manufacturing needs to be inclusive. In terms of governance, big data ethics is concerned with which types of inferences and predictions should be made using big data technologies such as algorithms.

Consent

If a consumer would like to use personal information, one needs expressed authorisation of what specific personal information moves to where, when and what purpose from the subject of the data. The subject of the information has the right to know how their data has been used. The consent must be given in an environment that is transparent, not implied. Just because a platform has been selected to chat does not mean that access to a list of contacts is required. The button and push notifications that are clicked to give permission should not be created in such a way that the automated system is opting in. For example, in binary choices if an individual button is less compact than the other, or if one button is concealed in the creation and the other jumps out, or if one button requires multiple clicks whereas the other is a single click.

Dynamic consent in the conversation of health and genomic study might assist a more effective consent methodology than once-off or broad informed consent, in terms of the issues outlined above.

Privacy

English On the privacy-conscientious use of mobile phone data

The global conversation on privacy is often unfairly layered to a simplified binary choice between entitled privacy and scientific progression. The marketing advertisements have even discharged critics of centralised data gathering, as withstanding advancement and holding on to history. Nevertheless, the advantages from scientific progression through data can be conquered in a manner dependable with privacy values as the past has been the case in epidemiological research. The extraction of value from data without compromising identity privacy is certainly possible technologically; e.g., by utilising homomorphic encryption and algorithmic design which makes reverse engineering difficult.

Currency

The business models propelling technology conglomerates have identified the opportunity of making the human identity the commodity to be consumed. While the tech services including search engines, communication channels and maps are provided for free, the new capital that has been uncovered in the procedure is personal data. There is an array of opinions about whether it is moral to receive capital in trading for having access to personal information. Similarities have been drawn between blood donations, where the rate of infectious blood donated declines when there is no financial payment for the blood donor. Additional questions arise around who should receive the profit from a data transaction?

Openness

The ideation of open information is centred around the notion that data should be freely accessible and should not have guidelines that would forbid its use, such as copyright laws. As of 2014 many global governments had started to produce open data packs for the purpose of translucency and ownership. This movement has gained traction via "open data activists" who have called for governments to make data packs attainable to allow the general public to withdraw meaning from the data and perform checks and balances themselves. King and Richards have argued that this call for transparency includes a tension between openness and secrecy.

Privacy concerns with social networking services

Since the arrival of social media in the early 2000s, online social networking platforms have grown rapidly, with the largest companies in social media in the mid-2010s being Facebook, Instagram, Twitter and Snapchat. The huge inundation of personal data that has become available on the web and stored in the cloud has placed consumer privacy at the forefront of conversation concerning the database's capacity to safely keep such personal data. The extent to which consumers and social media firms can access and utilise consumer profiles has become a new subject of moral consideration, and the legality, awareness, and boundaries of subsequent privacy violations are critical concerns in advance of the technological age

Electronic Privacy Information Center, Privacy Activism, Privacy Lives, and Privacy Rights Clearinghouse requesting changes to Facebook policy.

A social network is a social structure made up of a set of social actors (such as individuals or organisations), sets of dyadic ties, and other social interactions between actors. Privacy concerns with social networking services is a subset of data privacy, involving the right of mandating personal privacy concerning storing, re-purposing, provision to third parties, and displaying of information pertaining to oneself via the Internet. Social network security and privacy problems result from the huge amounts of data these online portals process each day. Applications that request consumers to participate in—messages, invitations, photos, open platform applications and other applications are often the arenas for others to gain acquire to a consumer's private data. In addition, the technologies needed to deal with user's information may intrude their privacy.

Causes

There are several origins that contribute to the invasion of privacy throughout social networking platforms. It has been recognized that “by design, social media technologies contest mechanisms for control and access to personal information, as the sharing of user-generated content is central to their function." This proves that social networking companies need private information to become public so their sites can operate. They require people to share and connect with each other. This may not necessarily be a bad thing; however, one must be aware of the privacy concerns. Even with privacy settings, posts on the internet can still be shared with people beyond a user's followers or friends. One reason for this is that “English law is currently incapable of protecting those who share on social media from having their information disseminated further than they intend." Information always has the chance to be unintentionally spread online. Once something is posted on the internet, it becomes public and is no longer private. Users can turn privacy settings on for their accounts; however, that does not guarantee that information will not go beyond their intended audience. Pictures and posts can be saved and posts may never really get deleted. In 2013, the Pew Research Center found that "60% of teenage Facebook users have private profiles.” This proves that privacy is definitely something that people still wish to obtain.

References

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