Study of the Temporal-Statistics-Based Reputation Models for Q&A Systems

Authors

  • Paulina Adamska Polish-Japanese Academy of Information Technology, Warsaw
  • Marta Juźwin Polish-Japanese Academy of Information Technology, Warsaw

DOI:

https://doi.org/10.7494/csci.2015.16.3.253

Keywords:

Q&A systems, reputation systems, expertise, online communities

Abstract

Q&A systems are becoming a vital source of knowledge in many different domains.  In some cases, they are also associated with services which provide employers with important information regarding the expertise of its potential employees. Therefore, the reputation earned in such communities can be associated with better job opportunities, and its significance is increasing. However, in a community where there is no direct financial motivation for participation, a reputation score is not solely an expertise metric. It is also a powerful motivator for remaining an active community member. Regardless of this complexity, algorithms for calculating reputation scores need to be as easy to understand (and implement) as possible. Therefore, the designers of the Q&A reputation system often implement a set of fixed rules, to some extent trading quality for quantity. Our goal is to study whether (and how) temporal statistics of a Q&A website can be incorporated into its reputation system. We want the proposed mechanism to dynamically adjust the impact of a single-answer evaluation on the reputation of its producer. We would like the proposed model to accurately reflect the expertise of content producers.

Downloads

Download data is not yet available.

References

Borzymek P., Sydow M., Wierzbicki A.: Enriching Trust Prediction Model in Social Network with User Rating Similarity. In: Ajith Abraham, Vaclav Snasel, eds, Proceedings of the 1st International Conference on Computational Aspects of Social Networks (CASoN 2009), pp. 40–47, IEEE Computer Society, Los Alamitos, NY, USA, 2009.

Bosu A., Corley C. S., Heaton D., Chatterji D., Carver J. C., Kraft N. A.: Building Reputation in StackOverflow: An Empirical Investigation. In: Proceedings of the 10th Working Conference on Mining Software Repositories, MSR ’13, pp. 89–92. IEEE Press, Piscataway, NJ, USA, 2013, http://dl.acm.org/citation.cfm?id=2487085.2487107.

Hanrahan B. V., Convertino G., Nelson L.: Modeling problem difficulty and expertise in stackoverflow. In: CSCW ’12 Computer Supported Cooperative Work, Seattle, WA, USA, February 11–15, 2012 – Companion Volume, pp. 91–94, 2012, http://dx.doi.org/10.1145/2141512.2141550.

Kao W., Liu D., Wang S.: Expert finding in question-answering websites: a novel hybrid approach. In: Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), Sierre, Switzerland, March 22-26, 2010, pp. 867–871, 2010, http://dx.doi.org/10.1145/1774088.1774266.

Kaszuba T., Hupa A., Wierzbicki A.: Advanced Feedback Management for Internet Auction Reputation Systems. IEEE Internet Computing, vol. 14(5), pp. 31–37, 2010, http://dx.doi.org/10.1109/MIC.2010.85.

McNally K., O’Mahony M. P., Smyth B.: A Model of Collaboration-based Reputation for the Social Web. In: Proceedings of the Seventh International Conference on Weblogs and Social Media, ICWSM 2013, Cambridge, Massachusetts, USA, July 8–11, 2013, 2013, http://www.aaai.org/ocs/index.php/ICWSM/ICWSM13/paper/view/6112.

Morzy M., Wierzbicki A.: The Sound of Silence: Mining Implicit Feedbacks to Compute Reputation. In: Internet and Network Economics, Second International Workshop, WINE 2006, Patras, Greece, December 15–17, 2006, Proceedings, pp. 365–376, 2006, http://dx.doi.org/10.1007/11944874_33.

Pal A., Harper F. M., Konstan J. A.: Exploring Question Selection Bias to Identify Experts and Potential Experts in Community Question Answering. ACM Transation Information Systems, vol. 30(2), p. 10, 2012, http://dx.doi.org/10.1145/2180868.2180872.

Romano D., Pinzger M.: Towards a Weighted Voting System for Q&A Sites. In: 2013 IEEE International Conference on Software Maintenance, Eindhoven, The Netherlands, September 22–28, 2013, pp. 368–371, 2013, http://dx.doi.org/10.1109/ICSM.2013.49.

Wierzbicki A.: The Case for Fairness of Trust Management. Electron. Notes Theor. Comput. Sci., vol. 197(2), pp. 73–89, 2008, http://dx.doi.org/10.1016/j.entcs.2007.12.018.

Downloads

Published

2015-09-07

How to Cite

Adamska, P., & Juźwin, M. (2015). Study of the Temporal-Statistics-Based Reputation Models for Q&A Systems. Computer Science, 16(3), 253. https://doi.org/10.7494/csci.2015.16.3.253

Issue

Section

Articles