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The myopia of crowds: Cognitive load and collective evaluation of answers on Stack Exchange

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  • Keith Burghardt
  • Emanuel F Alsina
  • Michelle Girvan
  • William Rand
  • Kristina Lerman

Abstract

Crowds can often make better decisions than individuals or small groups of experts by leveraging their ability to aggregate diverse information. Question answering sites, such as Stack Exchange, rely on the “wisdom of crowds” effect to identify the best answers to questions asked by users. We analyze data from 250 communities on the Stack Exchange network to pinpoint factors affecting which answers are chosen as the best answers. Our results suggest that, rather than evaluate all available answers to a question, users rely on simple cognitive heuristics to choose an answer to vote for or accept. These cognitive heuristics are linked to an answer’s salience, such as the order in which it is listed and how much screen space it occupies. While askers appear to depend on heuristics to a greater extent than voters when choosing an answer to accept as the most helpful one, voters use acceptance itself as a heuristic, and they are more likely to choose the answer after it has been accepted than before that answer was accepted. These heuristics become more important in explaining and predicting behavior as the number of available answers to a question increases. Our findings suggest that crowd judgments may become less reliable as the number of answers grows.

Suggested Citation

  • Keith Burghardt & Emanuel F Alsina & Michelle Girvan & William Rand & Kristina Lerman, 2017. "The myopia of crowds: Cognitive load and collective evaluation of answers on Stack Exchange," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-19, March.
  • Handle: RePEc:plo:pone00:0173610
    DOI: 10.1371/journal.pone.0173610
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    References listed on IDEAS

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    1. Imai, Kosuke & van Dyk, David A., 2005. "A Bayesian analysis of the multinomial probit model using marginal data augmentation," Journal of Econometrics, Elsevier, vol. 124(2), pages 311-334, February.
    2. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    3. Jain, Shaili & Chen, Yiling & Parkes, David C., 2014. "Designing incentives for online question-and-answer forums," Games and Economic Behavior, Elsevier, vol. 86(C), pages 458-474.
    4. Benjamin Scheibehenne & Rainer Greifeneder & Peter M. Todd, 2010. "Can There Ever Be Too Many Options? A Meta-Analytic Review of Choice Overload," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(3), pages 409-425, October.
    5. Soojung Kim & Sanghee Oh, 2009. "Users' relevance criteria for evaluating answers in a social Q&A site," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(4), pages 716-727, April.
    6. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    7. Ghosh, Arpita & Hummel, Patrick, 2014. "A game-theoretic analysis of rank-order mechanisms for user-generated content," Journal of Economic Theory, Elsevier, vol. 154(C), pages 349-374.
    8. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
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    Cited by:

    1. Kimmy Wa Chan & Stella Yiyan Li & Jian Ni & John JianJun Zhu, 2021. "What Feedback Matters? The Role of Experience in Motivating Crowdsourcing Innovation," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 103-126, January.
    2. Rohit Aggarwal & Michael J Lee & Braxton Osting & Harpreet Singh, 2021. "Improving Funding Operations of Equity‐based Crowdfunding Platforms," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4121-4139, November.

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