Roundtable: Social Media Users' Privacy Expectations & the Ethics of Using Their Data by Third Parties
Roundtable at the 2018 AoIR conference. Anatoliy Gruzd, Jenna Jacobson, Ryerson University, Canada Jacquelyn Burkell, Western University Joanne McNeish, Ryerson University Anabel Quan-Haase, Western University Abstract The transnational flows of information across nations and borders make it difficult to introduce and implement privacy-preserving policies relating to social media data. Social media data are a rich source of behavioural data that can reveal how we connect and interact with each other online in real time. Furthermore, the materiality of new digital intermediaries (such as the Internet of Things, AI, and algorithms) raises additional anticipated and unanticipated privacy challenges that need to be addressed as we continue to speed towards an increasingly digitally-mediated future. A by-product of the large-scale social media adoption is social media data mining; publicly available social media data is largely free and legally available to be mined, analyzed, and used (Kennedy 2016) for whatever purposes by third parties. Researchers have begun to suggest that ethics need to be considered even if the data is public (boyd & Crawford 2012). In the wake of the EU's recent legislation of the General Data Protection Regulation and the Right to be Forgotten, as well as increasing critical attention around the world, the roundtable will discuss how to navigate the transnational and material, as well as the complex and competing, interests associated with using social media, including ethics, privacy, security, and intellectual property rights. By balancing people's individual rights to exercise autonomy over "their" data and the societal benefits of using and analyzing the data for insights, the roundtable aims to generate theoretically-rich discussion and debate with internet researchers about the ethics, privacy, and best practices of using social media data.
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Roundtable: Social Media Users' Privacy Expectations & the Ethics of Using Their Data by Third Parties
- 1. Social Media Users' Privacy Expectations & the Ethics of Using Their Data by Third Parties Anatoliy Gruzd Jenna Jacobson Jacquelyn Burkell Joanne McNeish Anabel Quan-Haase @gruzd @jacobsonjenna @Profpaper @anabelquanhaase 1
- 3. 2B users 800M users 300M users Growth of Social Media Data @gruzd
- 4. The State of Social Media in Canada (Gruzd, Jacobson, Mai, & Dubois, 2018)
- 5. Social Media Data Stewardship Social Media Data + Data Stewardship = processes related to all aspects of managing social media data including Collection Storage Analysis Publishing Reuse Preservation @gruzd http://socialmediadata.org
- 6. Social Media Data Stewardship Social Media Data + Data Stewardship = processes related to all aspects of managing social media data including Collection Storage Analysis Publishing Reuse Preservation @gruzd Ethical Considerations http://socialmediadata.org
- 7. Ethical Considerations For Researchers Research more ‘acceptable’ if: • “it’s going to a good cause” • “morally right” • “general public good” • non-profit or academic Social media users care about data quality, accuracy, representation. Special consideration when studying sensitive topics and vulnerable groups (e.g., minors, the deceased, mental health). (Golder et al. 2017)
- 8. Ethical Considerations For Third Parties • Gruzd & Hernández-García. (2018). Privacy Concerns and Self-Disclosure in Private and Public Uses of Social Media. Cyberpsychology, Behavior, and Social Networking 21(7), 418–428. • Dubois, Gruzd, & Jacobson. (2018). Journalists’ Use of Social Media to Infer Public Opinion: The Citizens’ Perspective. Social Science Computer Review. • Jacobson & Gruzd. (2018). Employers’ Use of Young People’s Social Media: Extending Stakeholder Theory to Social Media Data. In Academy of Management Proceedings (Vol. 2018, p. 18217).
- 9. Survey of Online Adults in Canada • Academic researcher • Marketer • Financial institution • Employer • Journalist • Government • Legal professional • … • Credit check • Insurance claim • Public health monitoring • Law enforcement • Political polling • Suicide prevention • Tenant application review • … • Posting frequency • Location • Photos • Posts • Topics • Sentiment • Communication network • Friends’ list • … Who Why What data @jacobsonjenna (Gruzd, Jacobson, Mai, & Dubois, 2018)
- 10. Examples of Social Media Data Use Banks Who Determine credit score Why Aggregated data What data http://uk.businessinsider.com/yasaman-hadjibashi-at-barclays-africa-banks- using-big-data-and-social-media-2016-9@jacobsonjenna
- 11. Examples of Social Media Data Use Security Agency Who Identify real or potential threats Why Location- based information What data https://www.forbes.com/sites/kalevleetaru/2016/10/12/geofeedia-is-just-the-tip- of-the-iceberg-the-era-of-social-surveillence/#10b6941a40e2@jacobsonjenna
- 12. Examples of Social Media Data Use Car insurance company Who Price car insurance Why Facebook posts and likes What data https://www.theguardian.com/technology/2016/nov/02/admiral-to-price-car- insurance-based-on-facebook-posts@jacobsonjenna
- 13. Examples of Social Media Data Use Cambridge Analytica Who Political targeted ad campaigns Why Facebook user data What data https://www.theguardian.com/news/series/cambridge-analytica-files @jacobsonjenna
- 14. Comfort by Third Party How comfortable would you be if one of the following entities accessed information about you or posted by you publicly on social media? % Uncomfortable @jacobsonjenna
- 15. $ Comfort by DataType How comfortable would you be if a third party accessed the following information about you or posted by you publicly on social media? % Uncomfortable @jacobsonjenna
- 16. KeyTakeaways •Social media research ethics = not a ”one size fits all” framework •Privacy varies across uses, users, and data types •Ethical considerations for researchers using publicly available social media data @jacobsonjenna
- 17. 1. Introduction 2. Invited Panelists 3. Q&A Outline
- 18. Invited Panelists Jacquelyn Burkell Associate Professor, Western U Joanne McNeish Associate Professor, Ryerson U Anabel Quan-Haase Professor, Western U
- 19. Jacquelyn Burkell Complicating Privacy Attitudes Burkell and Fortier 2014
- 20. Study Purpose: to measure change in Facebook user attitudes and behaviour toward privacy after exposure to Data Selfie intervention Method: 214 Facebook users from large urban Canadian university Results: • Use of Data Selfie increased privacy concerns about organizations and other users • Increase in privacy concern was especially pronounced in those who completed study before Cambridge Analytica scandal • When Data Selfie was perceived to be an accurate and useful tool, information privacy-protective responses (IPPR) increased • Change in privacy concern, number of social media accounts, and exposure to Cambridge Analytica scandal did not predict users’ engagement in IPPR Knowledge May Not Be Power: The Difficult Job of Changing Facebook Users’ Behaviour @Profpaper (Gruzd, McNeish, Dahoah Halevi, & Phillips, Under Review).
- 21. Examples of social privacy concerns mentioned by our participants Examples of institutional privacy concerns noted by our study participants Examples of legitimacy privacy concerns expressed by our study participants • Losing control of one’s information and how it might be used • Giving out too much information • Not wanting the whole world knowing everything; what one is doing, location, personal things happening, etc. • Not wanting people knowing harmless things about one • Not wanting people knowing what is going on • Exposing oneself • Organizations collecting information about one • Organizations having one’s information–donation, adverting, marketing, political, insurance organizations • Organizations passing one’s name and information to someone else • Organizations selling one’s information • Government checking one’s Facebook • Being scammed • Unsolicited mail, junk mail or spam • Being hacked • Identity theft • Stealing one’s knowledge • Unauthorized/illegal access to one’s bank account • Unauthorized/illegal access to one’s credit card numbers (compromise of credit card number) • Stealing one’s credit card numbers • Virus/cookies • Wire tapping/surveillance • Intellectual property Types of Privacy Concerns of EastYork Older Adults (N=40) @anabelquanhaase
- 22. 1. Introduction 2. Invited Panelists 3. Q&A Outline
- 23. Social Media Users' Privacy Expectations & the Ethics of Using Their Data by Third Parties Anatoliy Gruzd Jenna Jacobson Jacquelyn Burkell Joanne McNeish Anabel Quan-Haase @gruzd @jacobsonjenna @Profpaper @anabelquanhaase 25
- 24. #SMSociety 400+ Authors 250+ Attendees 28 Countries