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Follow the reader: filtering comments on slashdot

Published:29 April 2007Publication History

ABSTRACT

Large-scale online communities need to manage the tension between critical mass and information overload. Slashdot is a news and discussion site that has used comment rating to allow massive participation while providing a mechanism for users to filter content. By default, comments with low ratings are hidden. Of users who changed the defaults, more than three times as many chose to use ratings for filtering or sorting as chose to suppress the use of comment ratings. Nearly half of registered users, however, never strayed from the default filtering settings, suggesting that the costs of exploring and selecting custom filter settings exceeds the expected benefit for many users. We recommend leveraging the efforts of the users that actively choose filter settings to reduce the cost of changing settings for all other users. One strategy is to create static schemas that capture the filtering preferences of different groups of readers. Another strategy is to dynamically set filtering thresholds for each conversation thread, based in part on the choices of previous readers. For predicting later readers' choices, the choices of previous readers are far more useful than content features such as the number of comments or the ratings of those comments.

References

  1. Ackerman, M.S., Swenson, A., Cotterill, S. and DeMaagd, K., I-DIAG: From Community Discussion to Knowledge Distillation. in Conference on Communities and Technologies, (2003). Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Adamic, L. and Glance, N., The Political Blogosphere and the 2004 U.S. Election: Divided They Blog. in 2nd Annual Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics, WWW2005, (Japan, 2005).Google ScholarGoogle Scholar
  3. Butler, B.S. Membership Size, Communication Activity, and Sustainability: A Resource-Based Model of Online Social Structures. Information Systems Research, 12 (4). 346--362. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Crawford, S., McCabe, S., Couper, M. and Boyd, C., From Mail to Web: Improving Response Rates and Data Collection Efficiencies. in International Conference on Improving Surveys, (Copenhagen, Denmark, 2002).Google ScholarGoogle Scholar
  5. Facca, F.M. and Lanzi, P.L. Mining interesting knowledge from weblogs: a survey. Data & Knowledge Engineering, 53 (3). 225--241. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Findlater, L. and McGrenere, J., A comparison of static, adaptive, and adaptable menus. in Conference on Human Factors in Computing Systems, (Vienna, Austria, 2004), ACM Press, 89--96. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Finholt, T.A. and Olson, G.M. From laboratories to collaboratories: A new organizational form for scientific collaboration. Psychological Science, 8. 28--36.Google ScholarGoogle Scholar
  8. Fisher, D.A. Social and Temporal Structures in Everyday Collaboration Information and Computer Science, University of California, Irvine, 2004, 214.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Goldberg, D., Nichols, D., Oki, B.M. and Terry, D. Using collaborative filtering to weave an information tapestry. Communications of the ACM, 35 (12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Jones, Q. and Rafaeli, S., User Population and User Contributions to Virtual Publics: A Systems Model. in GROUP'99, (Phoenix, AZ, 1999), ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Jones, Q., Ravid, G. and Rafaeli, S., An empirical exploration of mass interaction system dynamics: Individual information overload and Usenet discourse. in 35th Hawaii International Conference on System Sciences, (2002). Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Jones, Q., Ravid, G. and Rafaeli, S. Information Overload and the Message Dynamics of Online Interaction Spaces: A Theoretical Model and Empirical Exploration. Information Systems Research, 15 (2). 194--210. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Kelly, J., Fisher, D. and Smith, M., Debate, Division, and Diversity: Political Discourse Networks in USENET Newsgroups. in Online Deliberation 2005 / DIAC--2005, (Stanford, CA, 2005).Google ScholarGoogle Scholar
  14. Lampe, C. and Johnston, E., Follow the (Slash) dot: Effects of Feedback on New Members in an Online Community. in International Conference on Supporting Group Work, GROUP '05, (Sanibel Island, FL, 2005), ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Lampe, C. and Resnick, P., Slash(dot) and burn: distributed moderation in a large online conversation space. in Conference on Human Factors in Computing Systems (CHI), (Vienna, Austria, 2004), ACM Press, 543--550. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Mackay, W.E., Triggers and barriers to customizing software. in Conference on Human Factors in Computing Systems, (New Orleans, Louisiana, 1991), ACM Press, 153--160. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. March, J.G. and Simon, H.A. Organizations. John Wiley, New York, 1958.Google ScholarGoogle Scholar
  18. Miller, G.A. The Magical Number Seven, Plus or Minus Two: Some limits on our capacity for processing information. Psychological Review, 63 (2). 81--97.Google ScholarGoogle ScholarCross RefCross Ref
  19. Page, S.R., Johnsgard, T.J., Albert, U. and Allen, C.D., User customization of a word processor. in Conference on Human Factors in Computing Systems, (Vancouver, British Columbia, 1996), ACM Press, 340--346. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Resnick, P. Beyond Bowling Together: SocioTechnical Capital. in Carroll, J. ed. HCI in the New Millenium, Addison-Wesley, 2001.Google ScholarGoogle Scholar
  21. Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P. and Reidl, J., GroupLens: an open architecture for collaborative filtering of netnews. in ACM conference on Computer Supported Cooperative Work, (Chapel Hill, NC, 1994). Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Simon, H.A. Sciences of the Artificial. MIT Press, Cambridge, MA, 1996. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Smith, M. Measures and Maps of Usenet. in Lueg, C. and Fisher, D. eds. From Usenet to CoWebs: Interacting with Social Information Spaces, Springer Verlag, New York, NY, 2002.Google ScholarGoogle Scholar
  24. Terveen, L. and Hill, W. Beyond recommender systems: Helping people help each other. in Carroll, J.M. ed. HCI in the New Millennium, Addison-Wesley, New York, 2002.Google ScholarGoogle Scholar
  25. Viegas, F.B., Wattenberg, M. and Dave, K., Studying cooperation and conflict between authors with history flow visualizations. in Proceedings of the 2004 conference on Human factors in computing systems, (Vienna, Austria, 2004), ACM Press, 575--582. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Conferences
      CHI '07: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
      April 2007
      1654 pages
      ISBN:9781595935939
      DOI:10.1145/1240624

      Copyright © 2007 ACM

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      Publication History

      • Published: 29 April 2007

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      CHI '07 Paper Acceptance Rate182of840submissions,22%Overall Acceptance Rate6,199of26,314submissions,24%

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