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"Studying Eating Disorders in the Social Web: New methods, new questions" Antonio A. Casilli, LSE seminar 11 05 2010 Social Psychology Department

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Casilli lseisp110510 light

  1. 1. ISP SSS - LSE Lonfon, May 11th, 2010Studying Eating Disorders in the Social Web New methods, new questions Antonio A. Casilli, CEM, EHESS P Tubaro & AA Casilli Promesses et limites des SMA
  2. 2. • Edgar Morin Centre, School for Advanced Studies in Social Sciences (EHESS, Paris) http://en.wikipedia.org/wiki/Edgar _Morin_Centre• Interdisciplinary Institute for Contemporary Anthropology (IIAC, Paris)• Research topics: CMC and health - especially eating behaviors• Social network approach to eating disorders (ANAMIA project) P Tubaro & AA Casilli Promesses et limites des SMA
  3. 3. TOC• Pro-ED online communities• Our approach• Methods• Empirical data• Agent-based simulations• Conclusions P Tubaro & AA Casilli Promesses et limites des SMA
  4. 4. • Pro-ED online communities P Tubaro & AA Casilli Promesses et limites des SMA
  5. 5. • “Pro-ana”, “pro-mia”: controversial subcultures 6 advocating anorexia and 5 bulimia nervosa on the Search Volume Index 4 Ana_mia web 3 Pro_ana Pro_mia• A “movement”? A “skill”? 2• How to study this social 1 0 phenomenon? Ja M 22 Ju 27 5 Se 19 005 D 11 05 M 26 05 Ju 22 07 D 7 2 07 M 30 7 Ju 23 007 Se 15 08 N 7 2 08 Fe 4 2 005 Au 21 006 N 13 006 Ja 5 2 006 Ap 28 06 O 5 2 07 Fe 30 08 ec 2 ec 0 ov 0 ar 00 ay 2 ar 2 ov 2 ct 0 n n 2 l 1 20 n 20 p 20 p 20 n 0 b 0 b 20 g 2 r 20 22 0• How to devise suitable 20 8 0 09 public health tools and Evolution over four years of the search volume index for common ana-mia queries communication policies? (Source: Google Trends, March 12th 2009) P Tubaro & AA Casilli Promesses et limites des SMA
  6. 6. • Rough typology of online pro-ED websites: 1. Personal websites 2. Online social media/forums 3. ‘Cloaked’ websites 4. ‘Universities’• ‘Thinspiration’, self- help, advice P Tubaro & AA Casilli Promesses et limites des SMA
  7. 7. • Our approach P Tubaro & AA Casilli Promesses et limites des SMA
  8. 8. •The pro-ED population is: •relatively small; •vulnerable (health risk; underage); •partly hidden; •frequent migrations.•Large quantitative surveys & webcrawling possible only toan extent•Rely on smaller-scale, purposive samples for qualitativeenquiry P Tubaro & AA Casilli Promesses et limites des SMA
  9. 9. • Ongoing project (ANAMIA) : a social networks approach to pro-ED sociability• Social factors influencing health behaviours• Computer use influencing social factors• Focus on online/offine personal networks P Tubaro & AA Casilli Promesses et limites des SMA
  10. 10. • Methods P Tubaro & AA Casilli Promesses et limites des SMA
  11. 11. •A wide array of methods •Online ethnographies •Online experiments •Social network analysis •Web-based in-depth interviews •Multi-agent simulations•General framework: Ethnographically-informed social simulation (P Tubaro &AA Casilli BMS, 2010) P Tubaro & AA Casilli Promesses et limites des SMA
  12. 12. • Combining qualitative data and agent-based computer simulation: • enriches model with insight into actors behavior and motivations; • performs “thought experiments” to test consistency of theories; • replicates and generalizes findings from fieldwork; • supports cross-disciplinary validation of results. P Tubaro & AA Casilli Promesses et limites des SMA
  13. 13. • Starting point: an actual social process;• Qualitative sub-loop: formulate hypotheses, collect data,• adjust categories, until a theory is produced;• Design, build, code and de-bug an agent-based model;• Generate simulated data and revise theory;• This may direct back to the field (resample and re-start sub-loop). P Tubaro & AA Casilli Promesses et limites des SMA
  14. 14. • Empirical data P Tubaro & AA Casilli Promesses et limites des SMA
  15. 15. • Fieldwork with ana-mia subjects is currently at an early stage.• Data collected so far are exploratory, and include: – At micro level: a qualitative study of network tie formation on Facebook; – At macro level: a web cartography of the pro ED-sphere in France and UK• Use of preliminary data to inform and validate a first simulation. P Tubaro & AA Casilli Promesses et limites des SMA
  16. 16. • Facebook experiment• Creation of social structures (‘friendship’, ‘social capital’) through self-disclosure and adoption of cultural traits• 50 days (Apr. 27th, - Jun. 15th, 09)• Name generator and IOS to select subjects• An actual and a control profile send 50 friend requests• Recognizable name and picture• 15 reply (14 for control) P Tubaro & AA Casilli Promesses et limites des SMA
  17. 17. • “Friends” provide feedback on how to adapt profile – Comments – Private messages – Like – Share• “Friends” appreciate disclosure• Actual profile contains more personal information, images, interactive data• Control data contains sparse information P Tubaro & AA Casilli Promesses et limites des SMA
  18. 18. •Pete Warden, Nicholas Christakis :«harvesters» and «dataminers»•«Mark Zuckerberg has built hissocial networking empire on thebelief that "information wants to beshared", a particular philosophy ofinformation that directly impacts thevalues built into the design ofFacebook, ranging from its userinterface, privacy policies, terms ofservice, and method of governance »(Michael Zimmer)•Social media is ethically puzzling P Tubaro & AA Casilli Promesses et limites des SMA
  19. 19. Actual Profile Control Profile Starting point 11 05 09 P Tubaro & AA Casilli Promesses et limites des SMA
  20. 20. Actual Profile Control Profile Taste display 19 05 09 P Tubaro & AA Casilli Promesses et limites des SMA
  21. 21. Actual Profile Control Profile Personal information 22 05 09 P Tubaro & AA Casilli Promesses et limites des SMA
  22. 22. Actual Profile Control Profile Photo album online 13 06 09 P Tubaro & AA Casilli Promesses et limites des SMA
  23. 23. •Insight from preliminaryqualitative study is thatonline network formationmay depend upon: •Privacy settings, i.e. visibility of contents to others; •Self-display, i.e. personal and cultural traits exhibited and that traits may change with network composition.•The model aims toproblematize these factorsin simulated largernetworks. P Tubaro & AA Casilli Promesses et limites des SMA
  24. 24. • Agent-based simulations P Tubaro & AA Casilli Promesses et limites des SMA
  25. 25. •We focus on the impact of: •tendency to conformism vs. dissonance in cultural traits; •preference for bonding vs. bridging in tie formation; •possibility to limit incoming ties through privacy protection.•We measure impactthrough: •number and size of components; •homogeneity of traits within and between components; •evolution of privacy settings over time. P Tubaro & AA Casilli Promesses et limites des SMA
  26. 26. P Tubaro & AA Casilli Promesses et limites des SMA
  27. 27. •At initialization, each actor is endowed with: •a vector (several dimensions) of traits; •a privacy setting (visible/invisible).•Actors can be: •isolates; •connected;•If connected: •they share most traits with their contacts; •but may dffier on one dimension; •this depends on the ‘Dissonance’ parameter•We test the following values of parameters: Paramètres ValeursDissonance 0,01 0,03 0,08Seuil de bonding 0,20 0,50 0,70Privacy On Off P Tubaro & AA Casilli Promesses et limites des SMA
  28. 28. SETUP Tick t+1 Update z(Ai) ≠ µz (friendsi) Pick up random A N Is anom(A) < AnomThrshld? Y Create Tie Break Tie N N Create BreakIs µz(A)-µz (grp) < BBThrshd? Is µz(A)-µz (grp) ≥ BBThrshd? Bridging Tie Bridging Tie Y Y Create Break Bonding Tie Bonding Tie P Tubaro & AA Casilli Promesses et limites des SMA
  29. 29. • Simulation results (20,000 ticks): three stable configurations(1) Giant Component (2) Hegemony (3) Little Boxes P Tubaro & AA Casilli Promesses et limites des SMA
  30. 30. Number and size of components, varying Dissonance and Bonding Propensity, privacy protection on P Tubaro & AA Casilli Promesses et limites des SMA
  31. 31. Number and size of components, varying Dissonance and Bonding Propensity, privacy protection off P Tubaro & AA Casilli Promesses et limites des SMA
  32. 32. • Explain the effects of parameters – With lower propensity to bonding (=greater openness to – bridging), only one or few components emerge; – This effect is stronger with higher Dissonance; – With higher propensity to bonding, many small communities emerge; – In this case, differences in Dissonance have little impact; – With no privacy protection, these effects are slightly amplified, because more ties can be formed.• Explain changes in privacy over time – Agents restrict access only when a giant component appears; – This is the only case in which average privacy increases; – Otherwise, average privacy diminishes until there are no more isolates, then is stable. P Tubaro & AA Casilli Promesses et limites des SMA
  33. 33. Average Privacy over time, varying Dissonance and Bonding propensity P Tubaro & AA Casilli Promesses et limites des SMA
  34. 34. Structural signatures of learning dynamics 1. Inprinting 2. No learning 3. Mixed situation (no learning & continuous learning) P Tubaro & AA Casilli Promesses et limites des SMA
  35. 35. •Retrodictive validation•Web cartography of the pro ED-sphere in France and UK•Close to configuration 2‘Hegemony’ •Large component: personal pages and blogs of teenagers and young adults, strongly pro-ana; •Smaller components: different age groups and social positioning (cultural variance) •Homogeneity within components, heterogeneity between them. French pro-ED sphere (by Dr. Manuel Boutet) P Tubaro & AA Casilli Promesses et limites des SMA
  36. 36. •Retrodictive validation•Web cartography of the pro ED-sphere in France and UK•Close to configuration 2‘Hegemony’ •Large component: personal pages and blogs of teenagers and young adults, strongly pro-ana; •Smaller components: different age groups and social positioning (cultural variance) •Homogeneity within components, heterogeneity between them. British pro-ED sphere (by Dr. Manuel Boutet) P Tubaro & AA Casilli Promesses et limites des SMA
  37. 37. • Conclusions P Tubaro & AA Casilli Promesses et limites des SMA
  38. 38. • Preliminary results support the claim that agent-basedmodels can complement analyses based on smallqualitative fieldworks• Combine insight into social phenomenon andgeneralization of results• These methods are particularly useful with sensitiveand hidden populations.• These methods are particularly open to cross-disciplinary validation P Tubaro & AA Casilli Promesses et limites des SMA
  39. 39. Thank you!Contact me at:antonio [dot] casilli [at] ehess [dot] frFind this presentation on my research blog:http://www.bodyspacesociety.euFollow me on Twitter:http://www.twitter.com/bodyspacesoc P Tubaro & AA Casilli Promesses et limites des SMA

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