Talk at Workshop on Information Neworks, NYU Stern, 2011

1. Attention and bias in social information networks Scott counts, microsoft research

2. flickr: alshepmcr

4. Looking time per tweet is short, memory is poor.

5. Looking time per tweet is short, memory is poor.

6. Looking time per tweet is short, memory is poor.

7. Including links, RTs, heavy tweeting all decrease attention and/or interest.

8. Including links, RTs, heavy tweeting all decrease attention and/or interest.

9. Including links, RTs, heavy tweeting all decrease attention and/or interest.

10. Including links, RTs, heavy tweeting all decrease attention and/or interest.

11. Personal contacts increase attention and memory. Counts, S., & Fisher, K. (2011). Taking It All In? Visual Attention in Microblog Consumption. In Proc. ICWSM ‘11.

13. Problem statement How does a user’s name influence perception of her and her content?

14. Anonymous survey screen

15. Non-Anonymous survey screen

16. Results – author ratings Fairly bimodal distributions Downward shift in ratings when non-anonymous

17. Results – rating distribution Good author get higher ratings when non-anon. Bad authors hurt most by names Average authors similar to good (KL div = .02) but hurt by name (KL div = .23; p < .001)

18. Results – ratings & follower count Results tighten up with names: R2 = .16 -> .21 High follower count people get biggest boost Middle group hurt Pal, A., & Counts, S. (2011). What’s In a @Name? How Name Value Biases Judgment of Microblog Authors. In Proc. ICWSM ‘11.

19. Credibility and truth

20. Credibility and truth

21. Credibility and truth

22. Credibility and truth

23. Credibility and truth

24. Credibility and truth* Name type impacts tweet and author credibility Correlations between truth and tweet (r = .39) and author (r = .29) modest * Morris, M., Counts, S., Roseway, A., Hoff, A., & Schwartz, J. (2011). Under review.

25. Bringing it together

26. Bringing it together Minimal visual processing/attention Poor memory encoding

27. Bringing it together Minimal visual processing/attention Poor memory encoding Difficulty in determining truthfulness Systematic use of heuristics (biases) Friends Name value

28. Bringing it together Minimal visual processing/attention Poor memory encoding Difficulty in determining truthfulness Systematic use of heuristics (biases) Friends Name value ** Peripheral processing route **

29. Implications

30. Implications Effective reach of social media

31. Implications Effective reach of social media Information diffusion

32. Implications Effective reach of social media Information diffusion Social contagion: Stickiness* (increased adoption and sustained product use) and memory for content * Aral, S., & Walker, D. (2010). Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence Networks. Management Science.

33. Attention and bias in social information networks Scott counts, microsoft research

34. low level :: your brain on facebook* * Fisher, K., & Counts, S. (2010). Your Brain on Facebook: Neuropsychological Associations with Social Versus Other Media. In Proc. ICWSM ‘10.

35. social information networks :: levels of analysis Math/Theory Social media analytics Computer-Mediated Communication Social Cognition Physiological

36. Results – factors for bias: gender Most top authors are gender neutral (e.g., Time, Mashable) Men higher than women when anonymous, but drop more when names shown Women get slight bump when names shown Pal, A., & Counts, S. (2011). What’s In a @Name? How Name Value Biases Judgment of Microblog Authors. In Proc. ICWSM ‘11.

37. social information networks :: levels of analysis Math/Theory Social media analytics Computer-Mediated Communication Social Cognition Physiological

38. Problem statement How does a user’s name influence perception of her and her content?

39. Problem statement How does a user’s name influence perception of her and her content?