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Introduction Scientific goal – Investigate changing norms on personal data; identifying heavily targeted subgroups. Societal relevance – Information market.

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Presentation on theme: "Introduction Scientific goal – Investigate changing norms on personal data; identifying heavily targeted subgroups. Societal relevance – Information market."— Presentation transcript:

1 Introduction Scientific goal – Investigate changing norms on personal data; identifying heavily targeted subgroups. Societal relevance – Information market failure. Research questions – What does big data mean for online agency? Who is being tracked ? Theoretical Basis – The Political Economy of the Information Market. Key findings – On the web, online agents act in an environment of market failure; online agents agree to unconscionable contracts regarding the extraction and use of their personal data. Questions for you: What is your opinion on cookie technology? Have you ever heard of flashcookies? Evercookies? Browser fingerprinting? Canvas fingerprinting? How much of your personal data would like to have erased by social media or search companies? How many profiles would you choose if you could have multiple identities online? Methods content analysis of the online discussions in the IETF subgroup on HTML cookies and RFCs on HTTP State Management (1994-2011); multiple regression analysis; explorative analysis on newer web tracking technology; What Happens When You Use VoIP? “Skype may gather and use information about you, including (but not limited to) information in the following categories:” Multivariate Results Young(ish) people are more often racked (that is significant and linear). Higher educated higher income people are more often tracked (very straightforward). People with a paid job are less often tracked (seems to be changing, needs further check - so pls do not cite). **** Conclusions Online information market tends to display symptoms of market failure. Self-regulation is impossible because it would severely disadvantage a company. Unconscionable contracts are the only choice online users have. Web tracking leads to unequally targeted online populations. Sylvia E. Peacock Department of Social Science, York University, Toronto, Canada speacock@yorku.ca https://www.researchgate.net/profile/Sylvia_Peacock @SylviaPeacock1 Literature cited Barth, Adam. 2011. HTTP State Management Mechanism. RFC 6265. Online available at http://www.rfc-editor.org/rfc/rfc6265.txt [accessed July 2014]. Kristol, David M., Montulli, Lou. 1997. HTTP State Management Mechanism. RFC 2109, online available at http://rfc2109.openrfc.org/. Kristol, David M., Montulli, Lou. 2000. HTTP State Management Mechanism. RFC 2965, online available at http://rfc2965.openrfc.org/ [accessed July 2014]. Peacock, Sylvia E. 2014. What is Kind Midas Doing Online? User Agency in the Age of Big Data. Conference Presentation Atiner Conference, Athens, Greese, 4.-7. July 2014. Peacock, Sylvia E. 2014. The Used User: Online Agency in the Age of Big Data. Submitted Manuscript. Skype Privacy Policy. 2014. www.skype.com/en/legal/privacy (July/2014) Data information Statistics Canada. 2011. Canadian Internet Use Survey 2010. Machine readable data file. Statistics Canada. 2013. Canadian Internet Use Survey 2012. Machine readable data file. URL http://kristol.org/cookie/cookie-2.68.txt URL http://lists.w3.org/Archives/Public/ietf-http- wg-old/ © Basic poster template by Colin Purrington. Behavioral data Cookies, usage statistics, products and services ordered and delivered, statistics on page views, calling destinations; traffic data, i.e., duration of call, number calling, number called, content of instant messages, voice messages, video messages; access to other accounts on facebook, videos, Microsoft accounts, email, i.e. the electronic key provided by the services that acts in place of a password for authentication; Data about personal service provider Bandwidth, email address, IP address, phone number, mobile network, cell phone number, hotspot detection, error reports; Personal property data Computer type, computer capability, operating system, browser type, cell phone device model, manufacturer name, mobile operating system, cell usage, router device, router capability, connection information; Personal data Name, user ID, age, gender, language, list of contacts, Financial data Credit card number, banking information The VoIP User Source: skype.com/en/legal/privacy (July/2014) and Gingerbread man: veryicon.com/icons/holiday/christmas/ginger-man.html


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