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Re-examining price as a predictor of answer quality in an online q&a site

Published: 10 April 2010 Publication History

Abstract

Online question-answering services provide mechanisms for knowledge exchange by allowing users to ask and answer questions on a wide range of topics. A key question for designing such services is whether charging a price has an effect on answer quality. Two field experiments using one such service, Google Answers, offer conflicting answers to this question. To resolve this inconsistency, we re-analyze data from Harper et al. [5] and Chen et al. [2] to study the price effect in greater depth. Decomposing the price effect into two different levels yields results that reconcile those of the two field experiments. Specifically, we find that: (1) a higher price significantly increases the likelihood that a question receives an answer and (2) for questions that receive an answer, there is no significant price effect on answer quality. Additionally, we find that the rater background makes a difference in evaluating answer quality.

References

[1]
Adamic, L. A., Zhang, J., Bakshy, E. and Ackerman, M. S. Knowledge Sharing and Yahoo Answers: Everyone Knows Something. In Proc. WWW 2008, 2008.
[2]
Chen, Y., Ho, T. and Kim, Y. Knowledge Market Design: A Field Experiment on Google Answers. Journal of Public Economic Theory, Forthcoming.
[3]
Edelman, B. Earnings and Ratings at Google Answers. Manuscript, 2004.
[4]
Gazan, R. Specialists and Synthesists in a Question Answering Community. In Proc. American Society for Information Science and Technology, 2006.
[5]
Harper, F. M., Raban, D., Rafaeli, S. and Konstan, J. A. Predictors of Answer Quality in Online Q&A Sites. In Proc. CHI 2008, ACM Press, 2008.
[6]
Heckman, J. Sample selection bias as a specification error. Econometrica, 47(1), 153--162, 1979.
[7]
Mason, W., Watts, D. J. Financial Incentives and the "Performance of Crowds". In Proc. KDD-HCOMP '09, ACM Press, 2009.
[8]
Nam, K. K., Ackerman, M. S. and Adamic, L. A. Questions in, Knowledge iN? A Study of Naver's Question Answering Community. In Proc. CHI 2009, ACM Press, 2009.
[9]
Raban, D., The Incentive Structure in an Online Information Market. Journal of the American Society for Information Science and Technology, 59(14), 2284--2295, 2008.
[10]
Rafaeli, S., Raban, D. and Ravid, G. How Social Motivation Enhances Economic Activity and Incentives in the Google Answers Knowledge Sharing Market, International Journal of Knowledge and Learning, 2007
[11]
Regner, T. Why Voluntary Contributions? Google Answers! Technical Report, University of Jena, 2009.

Cited By

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  • (2024)What Constitutes a Helpful Health-Related Answer?Journal of Global Information Management10.4018/JGIM.34404432:1(1-35)Online publication date: 21-Jun-2024
  • (2024)Investigating the effects of nudges to promote knowledge-sharing behaviours on MOOC forums: a mixed method designBehaviour & Information Technology10.1080/0144929X.2024.2316287(1-26)Online publication date: 16-Feb-2024
  • (2023)Poverty Traps in Online Knowledge-Based Peer-Production CommunitiesInformatics10.3390/informatics1003006110:3(61)Online publication date: 13-Jul-2023
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      cover image ACM Conferences
      CHI '10: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
      April 2010
      2690 pages
      ISBN:9781605589299
      DOI:10.1145/1753326
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 10 April 2010

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      Author Tags

      1. information exchange
      2. information quality
      3. knowledge market
      4. online community
      5. question-answering

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      View all
      • (2024)What Constitutes a Helpful Health-Related Answer?Journal of Global Information Management10.4018/JGIM.34404432:1(1-35)Online publication date: 21-Jun-2024
      • (2024)Investigating the effects of nudges to promote knowledge-sharing behaviours on MOOC forums: a mixed method designBehaviour & Information Technology10.1080/0144929X.2024.2316287(1-26)Online publication date: 16-Feb-2024
      • (2023)Poverty Traps in Online Knowledge-Based Peer-Production CommunitiesInformatics10.3390/informatics1003006110:3(61)Online publication date: 13-Jul-2023
      • (2021)Power of Bonus in Pricing for CrowdsourcingProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/34910485:3(1-25)Online publication date: 15-Dec-2021
      • (2021)An efficient framework for blog recommender systemMaterials Today: Proceedings10.1016/j.matpr.2021.02.669Online publication date: Mar-2021
      • (2021)Exploring askers’ switching from free to paid social Q&A services: A perspective on the push-pull-mooring frameworkInformation Processing & Management10.1016/j.ipm.2020.10239658:1(102396)Online publication date: Jan-2021
      • (2021)Capacity pooling games in crowdsourcing servicesElectronic Commerce Research10.1007/s10660-021-09501-z23:2(1007-1047)Online publication date: 17-Jul-2021
      • (2018)Analyzing Payment-Driven Targeted Q8A SystemsACM Transactions on Social Computing10.1145/32814491:3(1-21)Online publication date: 10-Dec-2018
      • (2018)Pay-per-QuestionProceedings of the 2018 ACM International Conference on Supporting Group Work10.1145/3148330.3148332(1-11)Online publication date: 7-Jan-2018
      • (2017)Asking for more than an answerJournal of Information Science10.1177/016555151664553043:3(424-435)Online publication date: 1-Jun-2017
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