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What and how users read: Transforming reading behavior into valuable feedback for the Wikipedia community

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Most of the attention in previous research on the Wikipedia community has been devoted to the study of its production side: editors and their motivations, activity and roles. However, the value of the encyclopedia is also given by the millions of people who access it every day. In this work we focus on the - until now understudied - usage side of Wikipedia, investigating readers’ preference and behaviour as a precious source of information that can provide useful feedback to the editors’ community.

More information here: https://wikimania2014.wikimedia.org/wiki/Submissions/Who_reads_what_and_how:_Transforming_reading_behavior_into_valuable_feedback_for_the_Wikipedia_community

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What and how users read: Transforming reading behavior into valuable feedback for the Wikipedia community

  1. 1. What and how users read: Transforming reading preferences and behavior into valuable feedback for the Wikipedia community Wikimania 2014 | August 8, 2014 | Track: Wikimedia Inspiration Claudia Müller-Birn & Janette Lehmann! photo credit: marissa, CC BY 2.0
  2. 2. We know YOU! 2photo credit: philosophygeek CC BY-SA 2.0
  3. 3. 3 Included research papers: 477 Criteria of inclusion: Often cited Included years: 2003 - 2012 Number of groups: 6 Sources: English-language databases, peer-reviewed journal articles, doctoral theses Visualizationisbasedon(Okolietal.,2012)
  4. 4. 4 Included research papers: 477 Criteria of inclusion: Often cited Included years: 2003 - 2012 Number of groups: 6 Sources: English-language databases, peer-reviewed journal articles, doctoral theses Visualizationisbasedon(Okolietal.,2012)
  5. 5. ‣ Second-class members of an online community (Preece et al. 2004) ‣ “Lurkers” or “free-riders” 
 (e.g., Nonnecke, 2000, Nonnecke, 2004) ‣ More resource-taking than value- adding(Kollock, 1990) ‣ Only valuable when they become active contributors (Preece et al. 2004) 5 photo credit: claudia müller-birn, CC BY 2.0
  6. 6. Why might it be useful to know your readers better?! 6
  7. 7. Why might it be useful to know your readers better?! 7 As a user, I have a better reading experience, so I return more often, and eventually become a contributor. As an editor, I can use reading time 
 as an additional measure for article quality. As an author, I feel that my work is more valuable when an increasing number of readers access “my” articles. As an interface designer, I can adapt the article presentation by considering the exploration reading pattern. …
  8. 8. Let’s make the first step! 8photo credit: DonToofee CC BY-SA 2.0
  9. 9. 9 (1)We studied people’s reading preferences, i.e. what they read. ! !
  10. 10. Reading preferences 10 Biography Entertainment List Tech History Misc Health Leisure Sport Places Adult Culture/Belief 0 0.125 0.25 0.375 0.5 2.6% 2.6% 2.8% 3% 3.2% 3.4% 3.8% 4.4% 5% 7.6% 17.4% 44.2%
  11. 11. 11 (1)Does an article’s popularity change over time? ! ! people’s reading preferences
  12. 12. Three patterns of readers’ interests 12 2011-09 2011-12 2012-03 2012-06 2012-09 One direction Proportion of users 0 0.0020 Constant interest! ! ‣ Regularly accessed articles, sometimes only for fact finding ‣ Examples: Albert Einstein, Facebook, IMDB Peak interest! ! ‣ Death of people, game and movie releases ‣ Examples: Whitney Houston, The Hunger Games, 2012 Phenomenon Increasing/decreasing interest! ! ‣ Items that became popular/loose popularity during our observation period ‣ Examples: One direction, Instagram
  13. 13. 13
  14. 14. 14 (1)Does an article’s popularity change over time? ! (2)Do readers interests relate to editors preferences? ✔ people’s reading preferences
  15. 15. 15 Preference matrix
  16. 16. 16
  17. 17. 17 (1)We studied people’s reading preferences, i.e. what they read. ! (2)We analyzed people’s reading behaviors, 
 i.e. how they read. ✔
  18. 18. Example of a reading session on Wikipedia 18 0.5min 1.8min 2min Session statistics article views: 3 session articles: 5 reading time: 4.3min session starts session ends time
  19. 19. Two exemplary reading patterns 19 Focus Exploration ! ! Article Views ~ ↑↑ Reading Time ↑ ~ Session Articles ↓↓ ↑↑ ~ on average ↓ little below average ↑ little above average ↓↓ well below average ↑↑ far above average -1.0 0.5 -0.5 0.0 1.0 -1.0 0.5 -0.5 0.0 1.0
  20. 20. Explicit feedback with the AFT 20 Implicit feedback with reading behavior Readers give suggestions Readers read articles Editors make improvements Graphic created by Fabrice Florin, CC BY-SA 3.0
  21. 21. Wrapping up ‣ Data on readers are already available, but their potential has not being fully exploited ‣ Reading behavior provides an alternative way to think about readers but an application is not available yet 21photo credit: marissa, CC BY 2.0
  22. 22. ! Many thanks to the co-authors of our research paper: David Laniado, Mounia Lalmas, Andreas Kaltenbrunner ! For more information: http://janette-lehmann.de/docs/pub2014_ht.pdf Thank you. 22These slides are licensed under the Creative Commons Attribution-Share Alike 2.0 Generic license. Check out the review by Piotr on Wikimedia Research Newsletter (vol 4, issue 7, July 2014)
  23. 23. References ‣ C. Okoli, M. Mehdi, M. Mesgari, F. Å. Nielsen, and A. Lanamäki. The People’s Encyclopedia Under the Gaze of the Sages: A Systematic Review of Scholarly Research on Wikipedia. http://ssrn.com/ abstract=2021326, 2012. ‣ J. Preece, B. Nonnecke, and D. Andrews. The top five reasons for lurking: improving community experiences for everyone. Comp. in Human Behavior, 20(2), 2004. ‣ B. Nonnecke and J. Preece. Lurker demographics: counting the silent. In Proc. CHI (2000). ‣ B. Nonnecke, J. Preece and D. Andrews. What lurkers and posters think of each other. In Proc. HICSS (2004). ‣ P. Kollock. The economies of online cooperation: Gifts and public goods in cyberspace. In Communities in Cyberspace, pages 220–239. Routledge, 1990. 23These slides are licensed under the Creative Commons Attribution-Share Alike 2.0 Generic license.

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