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Evolution of Privacy in Online Social Networks

Explore the transformative journey of privacy settings in major social networks, focusing on Facebook's gradual shift towards user-controlled privacy and targeted advertising. Learn about the implications of default privacy settings changes and strategies for adaptation in the evolving landscape of online social platforms.

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Evolution of Privacy in Online Social Networks

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  1. Evolution of Privacy in Online Social Networks Ben Zimmerman CS2650: Distributed Multimedia Systems Fall 2010

  2. Major Social Networks • Facebook • Youtube • MySpace • LinkedIn (career-based) • Foursquare (location-based) • Latitude (location-based)

  3. The Facebook • Started in 2004 • Aimed at college students • Required a .edu email account • Had “segregated” networks for each school • Photo-sharing and tagging • Could specify your residence hall, class schedule

  4. Facebook 2.0 (2008-09) • Became the social network for everyone to be apart of • Addition of geographically-related networks • Privacy settings related to your network memberships • “Network X can see attribute Y about me” • The Status Update incorporated • Similar to what Twitter was already doing for years

  5. Facebook 3.0 (2010) • Privacy controls no longer related to networks • Privacy is controlled on granularity of friends, friends-of-friends, family, co-workers, regardless of what networks they belong to • “Friends can see my wall posts” • “Family members cannot view this photo album”

  6. Targeted Advertising • Facebook has always been free for its users to access • Supported by ad revenue • The wealth of personal info like interests in movies, music, books allows for effective advertising • As Facebook aimed to generate more revenue privacy changes occurred to allow greater access for outside vendors to information

  7. Changes in Facebook’s Default Privacy Settings • http://mattmckeon.com/facebook-privacy/

  8. Information Revelation Source: Gross, Ralph & Alessandro Acquisti. “Information Revelation and Privacy in Online Social Networks”

  9. Privacy Implications Source: Gross, Ralph & Alessandro Acquisti. “Information Revelation and Privacy in Online Social Networks” • Real-world location “check-ins” are becoming increasingly used in networks

  10. Social Networks as SIS • Natural slow intelligence systems • Consists of two entities/groups, each with own SIS characteristics • The SN as a business • The Users of the SN for interaction with peers • Currently, heavy focus on privacy due to wealth of personal information about each user

  11. Enumeration • The SN: as a business, considers ways of changing its features to attract revenue • In the past, geared towards targeted advertising which required mining users’ personal data • The users: have choices such as continuing to use, reducing usage, leaving, increasing usage, changing privacy settings (if available) • Mainly due to the changes in privacy that will occur

  12. Concentration • SN: decides to implement one of the strategies considered in the enumeration phase • Users: decide what their behavior will be in the future because of their preferences to privacy

  13. Adaptation • SN: implements the features it decided on • This is where a complimentary cycle begins of considering how the users react to the changes • Users: react to the changes according to their preferences by either altering their online habits or changing settings or information available

  14. Propagation • SN: makes users aware of changes via updates to the EULA • Users: voice their opinions within the network itself (as well as other mediums) with the possibility of changing others opinions by doing so

  15. Elimination • SN: decides to not pursue/consider certain options in the future. • May also be elimination of features/control for users • Consider it a changing of business policies • Users: someleave the network, or become very infrequent users

  16. Network Petri Net

  17. User Petri Net

  18. Prototype Model

  19. Refined Model

  20. Additions to Refined Model • Sinks for business policies, users, and user behaviors • Capacity of 1 set for all SIS components (Enumerator, Concentrator, etc.)

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