The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Knowledge sharing and yahoo answers: everyone knows something
Abstract
Yahoo Answers (YA) is a large and diverse question-answer forum, acting not only as a medium for sharing technical knowledge, but as a place where one can seek advice, gather opinions, and satisfy one's curiosity about a countless number of things. In this paper, we seek to understand YA's knowledge sharing and activity. We analyze the forum categories and cluster them according to content characteristics and patterns of interaction among the users. While interactions in some categories resemble expertise sharing forums, others incorporate discussion, everyday advice, and support. With such a diversity of categories in which one can participate, we find that some users focus narrowly on specific topics, while others participate across categories. This not only allows us to map related categories, but to characterize the entropy of the users' interests. We find that lower entropy correlates with receiving higher answer ratings, but only for categories where factual expertise is primarily sought after. We combine both user attributes and answer characteristics to predict, within a given category, whether a particular answer will be chosen as the best answer by the asker.
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Cites
The top five reasons for lurking: improving community experiences for everyone
Preece, J., Nonnecke, B., & Andrews, D. (2004) · Computers in Human Behavior · doi:10.1016/j.chb.2003.10.015 · Cited by 1,038
Cited by
Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., et al. (2009) · Science · doi:10.1126/science.1167742 · Cited by 3,365
Self-citationUncovering social spammers: social honeypots + machine learning
Lee, K., Caverlee, J., & Webb, S. (2010) · Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/1835449.1835522 · Cited by 619
The labor economics of paid crowdsourcing
Horton, J. J., & Chilton, L. B. (2010) · Proceedings of the 11th ACM conference on Electronic commerce · doi:10.1145/1807342.1807376 · Cited by 601
Reputation-based incentive protocols in crowdsourcing applications
Zhang, Y., & van der Schaar, M. (2012) · 2012 Proceedings IEEE INFOCOM · doi:10.1109/infcom.2012.6195597 · Cited by 315
Web credibility assessment: Conceptualization, operationalization, variability, and models
Choi, W., & Stvilia, B. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23543 · Cited by 168
Metadata
- Authors
- Adamic, L. A., Zhang, J., Bakshy, E., & Ackerman, M. S.
- Venue
- Proceedings of the 17th international conference on World Wide Web
- Publisher
- ACM
- Published
- 2008-04-21
- Pages
- 665-674
- OpenAlex
- W2129251351
- Cited by
- 732
- References
- 1
- FWCI
- 44.59
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Adamic, L. A., Zhang, J., Bakshy, E., & Ackerman, M. S. (2008). Knowledge sharing and yahoo answers: everyone knows something. Proceedings of the 17th international conference on World Wide Web. https://doi.org/10.1145/1367497.1367587
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