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Fragmentation of identity through structural holes in email contacts

Explore how social network structure impacts individual identity construction online through fragmentation and multi-faceted aspects. Observing behavior in email context reveals managing faceted selves and structuring social networks via email etiquette. Dive into visualizations of recipient connections to understand identity complexities.

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Fragmentation of identity through structural holes in email contacts

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  1. Fragmentation of identity through structural holes in email contacts danah boyd, Jeff Potter, Fernanda Viegas (Sociable Media, MIT Media Lab) danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  2. Research Questions • How does social network structure impact individual construction of identity? • How is this behavior made explicit online? • How can this be observed within the context of email? danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  3. Construction of Individual Identity • Interrelated ideas of identity • Social identity: public presentation of self • Internal identity: private view of self • Fragmentation vs. Multi-Faceted Identity • Fragmentation: conflicting internal identity • Multi-faceted: coherent internal identity, fragmented social identity danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  4. Managing Faceted Selves • Differentiated presentation changed according to context • How? Fashion, language, location/context, people • Why? Privacy, social appropriateness, reputation differentiation • Who? Dependent on self-monitoring habits, marginalization, fear of retribution • Fragmented social network (e.g., work, clubs, family, …) • Separate social circles provide for segmentation of presentation danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  5. Identity online • Confusion of context • Ease of moving between multiple contexts • Data aggregated across “locations” • Email address serves as context • Allows for privacy and faceted behavior danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  6. Relating Network Structure • Structural holes & bridges (Burt) • Maximize & control information flow • Simmelian ties (Krackhardt) • In public settings, personally constraining by restricting appropriate behavior – aggregate of all associations • Control of network structure • Minimize uncontrolled personal information flow danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  7. Structuring social networks via email • Recognizing the power of multiple recipients • Copy/paste phenomenon to appear personal or contextual • Slight content alternations for context • Making others aware of audience danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  8. Ego-Centric Visualization • Visualization tool to observe social networks embedded in email • Focused on structure • Analyzed “Mike’s” email habits • 5 years worth of complete data • Maintains multiple email addresses for different contexts • (Dis)advantages of using one person’s behaviors danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  9. Introducing Mike • Social characteristics: • 24-year old, gay-identified, white male • Born in northern CA, attended Yale (art & computer science) • Friends & jobs in: Boston, SF, Chicago, NYC • Uses many forms of media to stay connected • Mike’s primary social communities: • Family, high school friends • Undergraduate friends • Gay men in/outside Boston, in NYC • Boston, Texas, California work colleagues danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  10. Mike’s dataset • 80,941 messages • 1.03 average recipients per msg • 15,537 unique people • 7,250 people w/ 2,618 knowledge ties (excluding listservs) • 662,078 ties between all respondents (using only messages with <50 recipients; otherwise, 11.7 million) • 226 trusted ties; 23 reciprocal danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  11. Defining Connectivity • Knowledge ties • If A sends a message to B, A ‘knows’ B • Bdoes not necessarily know A • Awareness ties • If B receives a message from A -> B is ‘aware’ of A • If B and C both receive a message from A -> B and C are ‘aware’ of each other • Trusted ties • If A sends a message to B and blind carbon copies (BCC’s) D -> A ‘knows’ and ‘trusts’ D • (D has the ability to respond and reveal that A included people without B’s awareness) danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  12. Visualizations danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  13. Visualizations: Overview • Goal is to allow one to quickly see how Mike’s network is connected and view structural holes • Methodology • Spring/Wire explanation • View of entire world • Close-up views of network danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  14. Visualizations: Methodology • Basic spring/node algorithm used to place nodes in optimal location • - annealing algorithms don’t work with 15,000 nodes • Colors are used to indicate the relationship to the person • - based on which of Mike’s email address the person uses • - most common address used danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  15. Visualizations: Spring/Node (1/2) • Basic spring algorithm used to place nodes • -Ties act as springs, pulling connected nodes closer together • -Nodes act like magnets and repel each other danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  16. Visualizations: Spring/Node (2/2) • All nodes start out at random location, spring algorithm is run several hundred iterations • This (eventually) results in connected nodes being nearby and non-connected being far away danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  17. danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  18. Visualization: Entire World (1/2) • Color key for • all images danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  19. danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

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  22. danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

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  25. Social Implications • Using one person’s email, we can observe the social networks of hundreds of people - what are the implications of this? danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  26. Thoughts moving forward • More detailed analysis • Use visualizations to have ethnographic conversation with Mike • Extend to multiple users • Visual comparison valuable • Allow for interactivity • More detailed analysis of ego-centric graphs • Learn more from social network analysts danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

  27. http://smg.media.mit.edu/projects/SocialFragments/ danah boyd, Jeff Potter, Fernanda Viegas . Sociable Media, MIT Media Lab . Sunbelt . 17 February 2002

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