Cliff Lampe
Paul Resnick
ABSTRACT
Can a system of distributed moderation quickly and consistently separate high and low quality comments in an online conversation? Analysis of the site Slashdot.org suggests that the answer is a qualified yes, but that important challenges remain for designers of such systems. Thousands of users act as moderators. Final scores for comments are reasonably dispersed and the community generally agrees that moderations are fair. On the other hand, much of a conversation can pass before the best and worst comments are identified. Of those moderations that were judged unfair, only about half were subsequently counterbalanced by a moderation in the other direction. And comments with low scores, not at top-level, or posted late in a conversation were more likely to be overlooked by moderators.
- Avery, C., P. Resnick, and R. Zeckhauser, The Market for Evaluations. American Economic Review, 1999. 89(3): p. 564--584.Google Scholar
- Banerjee, A., A Simple Model of Herd Behavior. Quarterly Journal of Economics, 1992. 107(3): p. 797--818.Google Scholar
- Bikhchandani, S., D. Hirshleifer, and I. Welch, A Theory of Fads, Fashion, Custom and Cultural Change as Informational Cascades. Journal of Political Economy, 1989. 100(5): p. 992--1026.Google Scholar
- Butler, B., When is a group not a group: An empirical examination of metaphors for online social structure. 1999, Carnegie Mellon University: Pittsburgh.Google Scholar
- Friedman, E.J. and P. Resnick, The Social Cost of Cheap Pseudonyms. Journal of Economics and Management Strategy, 1997. 10(2): p. 173--179.Google Scholar
- Goldberg, D., et al., Using collaborative filtering to weave an information tapestry. Communications of the ACM, 1992. 35(12). Google ScholarDigital Library
- Grice, H.P., Utterer's meaning and intentions. Philosophical Review, 1969. 78: p. 147--177.Google Scholar
- Jones, Q., G. Ravid, and S. Rafaeli. An empirical exploration of mass interaction system dynamics: Individual information overload and Usenet discourse in 35th Hawaii International Conference on System Sciences. 2002. Google ScholarDigital Library
- Kollock, P. and M. Smith, Managing the Virtual Commons: Cooperation and Conflict in Computer Communities, in Computer-Mediated Communication: Linguistic, Social, and Cross-Cultural Perspectives, S. Herring, Editor. 1996, John Benjamin: Amsterdam.Google Scholar
- Malda, R., Slashdot FAQ, . 2003, http://slashdot.orgGoogle Scholar
- Pfaffenberger, B., A Standing Wave in the Web of Our Communications: Usenet and the Socio-Technical Construction of Cyberspace Values, in From Usenet to CoWebs: Interacting with Social Information Spaces, C. Lueg and D. Fisher, Editors. 2002, Springer Verlag: New York, NY.Google Scholar
- Resnick, P., et al. GroupLens: an open architecture for collaborative filtering of netnews. In ACM conference on Computer Supported Cooperative Work. 1994. Chapel Hill, NC. Google ScholarDigital Library
- Sack, W., Conversation map: An interface for very large-scale conversations. Journal of Management information Systems, 2000. 17(3): p. 73--92. Google ScholarDigital Library
- Shardanand, U. and P. Maes. Social information filtering: algorithms for automating "word of mouth" in SIGCHI conference on Human factors in computing systems. 1995. Denver, CO. Google ScholarDigital Library
- Smith, M.A. and A.T. Fiore. Visualization components for persistent conversations. in SIGCHI conference on Human factors in computing systems. 1991. Seattle, WA: ACM Press. Google ScholarDigital Library
- Terveen, L. and W. Hill, Beyond recommender systems: Helping people help each other, in HCI in the New Millennium, J.M. Carroll, Editor. 2001, Addison-Wesley: New York.Google Scholar
- Whittaker, S., et al. The Dynamics of Mass Interaction, in Proc. of Computer-Supported Cooperative Work. 1998. Seattle Washington: ACM. Google ScholarDigital Library
Index Terms
-
Slash(dot) and burn: distributed moderation in a large online conversation space
-
Recommendations
-
Follow the (slash) dot: effects of feedback on new members in an online community
GROUP '05: Proceedings of the 2005 ACM International Conference on Supporting Group WorkMany virtual communities involve ongoing discussions, with large numbers of users and established, if implicit rules for participation. As new users enter communities like this, both they and existing members benefit when new users learn the standards ...
-
Conversational Collaborative Recommendation --- An Experimental Analysis
Traditionally, collaborative recommender systems have been based on a single-shot model of recommendation where a single set of recommendations is generated based on a user's (past) stored preferences. However, content-based recommender system research ...
-
Collaborative filtering for orkut communities: discovery of user latent behavior
WWW '09: Proceedings of the 18th international conference on World wide webUsers of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such websites grows over time, users have even greater need for effective community recommendations ...
Comments