Skip to main content

Modeling Answerer Behavior in Collaborative Question Answering Systems

  • Conference paper
Advances in Information Retrieval (ECIR 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6611))

Included in the following conference series:

Abstract

A key functionality in Collaborative Question Answering (CQA) systems is the assignment of the questions from information seekers to the potential answerers. An attractive solution is to automatically recommend the questions to the potential answerers with expertise or interest in the question topic. However, previous work has largely ignored a key problem in question recommendation - namely, whether the potential answerer is likely to accept and answer the recommended questions in a timely manner. This paper explores the contextual factors that influence the answerer behavior in a large, popular CQA system, with the goal to inform the construction of question routing and recommendation systems. Specifically, we consider when users tend to answer questions in a large-scale CQA system, and how answerers tend to choose the questions to answer. Our results over a dataset of more than 1 million questions draw from a real CQA system could help develop more realistic evaluation methods for question recommendation, and inform the design of future question recommender systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adamic, L.A., Zhang, J., Bakshy, E., Ackerman, M.S.: Knowledge sharing and yahoo answers: everyone knows something. In: WWW, pp. 665–674 (2008)

    Google Scholar 

  2. Agichtein, E., Castillo, C., Donato, D., Gionis, A., Mishne, G.: Finding high-quality content in social media. In: WSDM, pp. 183–194 (2008)

    Google Scholar 

  3. Aperjis, C., Huberman, B.A., Wu, F.: Harvesting collective intelligence: Temporal behavior in yahoo answers (January 2010), http://arxiv.org/abs/1001.2320

  4. Bian, J., Liu, Y., Agichtein, E., Zha, H.: Finding the right facts in the crowd: factoid question answering over social media. In: WWW, pp. 467–476 (2008)

    Google Scholar 

  5. Bouguessa, M., Dumoulin, B., Wang, S.: Identifying authoritative actors in question-answering forums: the case of yahoo! answers. In: KDD (2008)

    Google Scholar 

  6. Cao, X., Cong, G., Cui, B., Jensen, C.S., Zhang, C.: The use of categorization information in language models for question retrieval. In: CIKM, pp. 265–274 (2009)

    Google Scholar 

  7. Cao, Y., Duan, H., Lin, C.Y., Yu, Y., Hon, H.W.: Recommending questions using the mdl-based tree cut model. In: WWW, pp. 81–90 (2008)

    Google Scholar 

  8. Gayo-Avello, D.: A survey on session detection methods in query logs and a proposal for future evaluation. Inf. Sci. 179(12), 1822–1843 (2009)

    Article  Google Scholar 

  9. Guo, J., Xu, S., Bao, S., Yu, Y.: Tapping on the potential of q&a community by recommending answer providers. In: CIKM, pp. 921–930 (2008)

    Google Scholar 

  10. Guo, L., Tan, E., Chen, S., Zhang, X., Zhao, Y.E.: Analyzing patterns of user content generation in online social networks. In: KDD, pp. 369–378 (2009)

    Google Scholar 

  11. Gyöngyi, Z., Koutrika, G., Pedersen, J., Garcia-Molina, H.: Questioning yahoo! answers. In: Proc. of the 1st Workshop on Question Answering on the Web (2008)

    Google Scholar 

  12. He, D., Göker, A.: Detecting session boundaries from web user logs. In: Proc. of the BCS-IRSG 22nd Annual Colloquium on Information Retrieval Research (2000)

    Google Scholar 

  13. Horowitz, D., Kamvar, S.D.: The anatomy of a large-scale social search engine. In: WWW, pp. 431–440 (2010)

    Google Scholar 

  14. Jeon, J., Croft, W.B., Lee, J.H.: Finding similar questions in large question and answer archives. In: CIKM, pp. 84–90 (2005)

    Google Scholar 

  15. Joachims, T.: Training linear svms in linear time. In: KDD, pp. 217–226 (2006)

    Google Scholar 

  16. Jurczyk, P., Agichtein, E.: Discovering authorities in question answer communities by using link analysis. In: CIKM, pp. 919–922 (2007)

    Google Scholar 

  17. Liu, M., Liu, Y., Yang, Q.: Predicting best answerers for new questions in community question answering. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds.) WAIM 2010. LNCS, vol. 6184, pp. 127–138. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  18. Liu, Q., Liu, Y., Agichtein, E.: Exploring web browsing context for collaborative question answering. In: IIiX, pp. 305–310 (2010)

    Google Scholar 

  19. Liu, X., Croft, W.B., Koll, M.: Finding experts in community-based question-answering services. In: CIKM, pp. 315–316 (2005)

    Google Scholar 

  20. Nam, K.K., Ackerman, M.S., Adamic, L.A.: Questions in, knowledge in?: a study of naver’s question answering community. In: CHI, pp. 779–788 (2009)

    Google Scholar 

  21. Qu, M., Qiu, G., He, X., Zhang, C., Wu, H., Bu, J., Chen, C.: Probabilistic question recommendation for question answering communities. In: WWW (2009)

    Google Scholar 

  22. Suryanto, M.A., Lim, E.P., Sun, A., Chiang, R.H.L.: Quality-aware collaborative question answering: methods and evaluation. In: WSDM, pp. 142–151 (2009)

    Google Scholar 

  23. Zhang, J., Ackerman, M.S., Adamic, L.: Expertise networks in online communities: structure and algorithms. In: WWW, pp. 221–230 (2007)

    Google Scholar 

  24. Zhou, Y., Cong, G., Cui, B., Jensen, C.S., Yao, J.: Routing questions to the right users in online communities. In: ICDE, pp. 700–711 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Liu, Q., Agichtein, E. (2011). Modeling Answerer Behavior in Collaborative Question Answering Systems. In: Clough, P., et al. Advances in Information Retrieval. ECIR 2011. Lecture Notes in Computer Science, vol 6611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20161-5_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-20161-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20160-8

  • Online ISBN: 978-3-642-20161-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics