Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

It's a Man's Wikipedia?

1,398 views

Published on

Vortrag, Wikipedianischer Salon in Berlin 2015, Studie, GESIS, CSS

Published in: Social Media
  • Be the first to comment

  • Be the first to like this

It's a Man's Wikipedia?

  1. 1. Claudia Wagner Berlin, March 2015 It's a Man's Wikipedia?
  2. 2. Who are your life heroes?
  3. 3. How did you learn about them?
  4. 4. The heroes we share are the heroes we have
  5. 5. Our Study • Compare for men and women: – Coverage – Lexical Presentation – Structural Position – Visibility Claudia Wagner, David Garcia, Mohsen Jadidi and Markus Strohmaier, It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopedia, The International AAAI Conference on Web and Social Media (ICWSM2015)
  6. 6. Coverage
  7. 7. Coverage in 2011 • Britannica versus Wikipedia Coverage – Reference Lists: e.g. The Atlantic’s 100 most influential figures in American history – Wikipedia misses 13% of women and 5% of men – Britannica misses 49% of women and 33% of men – Wikipedia’s coverage is more exhaustive – Women have a 2.6 (13/5) greater odds of omission in Wikipedia and a 1.48 (49/33) greater odds of omission in Britannica Reagle, Joseph; Rhue, Lauren (2011). "Gender Bias in Wikipedia and Britannica". International Journal of Communication (Joseph Reagle & Lauren Rhue) 5: 1138–1158.
  8. 8. Our Study: Data • 11% women in Freebase • 3% women in HA (people who made contributions to arts and science prior than 1950) • 13% women in pantheon
  9. 9. Coverage
  10. 10. Visibility
  11. 11. Visibility
  12. 12. Visibility
  13. 13. Structure
  14. 14. Asymmetry L(from=M, to=W) = -0.26 L(from=W, to=M) = -0.14
  15. 15. Asymmetry
  16. 16. Asymmetry
  17. 17. Assortativity L(from=M, to=M) = 0.28 L(from=W, to=M) = 0.15
  18. 18. Assortativity
  19. 19. Assortativity
  20. 20. Importance
  21. 21. So what?!?! Algorithms often use structural properties to determine importance (e.g. Page Rank) – Researchers need to understand social consequences of algorithms – 28. Feb 2015: “Google wants to rank websites based on facts not links”, NewScientist http://www.newscientist.com/article/mg22530102.600-google-wants-to- rank-websites-based-on-facts-not-links.html
  22. 22. Page Rank Eom YH, Aragón P, Laniado D, Kaltenbrunner A, Vigna S, et al. (2015) Interactions of Cultures and Top People of Wikipedia from Ranking of 24 Language Editions. PLoS ONE 10(3): e0114825. doi:10.1371/journal.pone.0114825 http://127.0.0.1:8081/plosone/article?id=info:doi/10.1371/journal.pone.0114825
  23. 23. Text
  24. 24. Finkbeiner Test http://en.wikipedia.org/wiki/Finkbeiner_test
  25. 25. Discriminative Words (DE) Women • Autorin • Ehemann • Künsterlin • Gatte • Schriftstellerin • Herzoging • Weiblich • Tänzerin • Schauspielerin • Mrs • Großmutter • Tante • Miss • Heirat • Freundin • Prinzessin • Gemahlin Men • Befördert • Reprasentantenhaus • Directory • Amtszeit • Republican • Division • Senat • Gouverneur • Congress • Biographical • Mannschaft • Rechtsanwalt • Senator • Expedition • Demokrat • Professor
  26. 26. Text
  27. 27. Discriminative Words (EN)
  28. 28. Discriminative Words (ES)
  29. 29. Text “Biographies of women on Wikipedia disproportionately focus on marriage and divorce compared to those of men.” David Bamman, Noel Smith. "Unsupervised Discovery of Biographical Structure from Text", Transactions of the Association for Computational Linguistics, 2, 2014 (pp. 363–376), p. 369:
  30. 30. Summary • Good News: – Visibility and Coverage of women looks good • Bad News: – Structural Inequality  what are the consequences? – How women are portrayed needs to be improved http://en.m.wikipedia.org/wiki/User:GGTF/Writing_about_women
  31. 31. Article-Writing Interaction Graph Evolution WikiWho and WikiVis wikiwho Fabian Flöck
  32. 32. WikiWho Plugin Fabian Flöck
  33. 33. WhoVis Fabian Flöck
  34. 34. Future Questions… • What causes the bias? – Wikipedia bias versus general media bias? – Male versus female editors? • Bias over time – Does the community improve?
  35. 35. Thank You claudia.wagner@gesis.org fabian.flöck@gesis.org Infos zu WikiWho and WikiVis http://f-squared.org/wikiwho/

×