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Evidence of Online Performance Deterioration in User Sessions on Reddit

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  • Philipp Singer
  • Emilio Ferrara
  • Farshad Kooti
  • Markus Strohmaier
  • Kristina Lerman

Abstract

This article presents evidence of performance deterioration in online user sessions quantified by studying a massive dataset containing over 55 million comments posted on Reddit in April 2015. After segmenting the sessions (i.e., periods of activity without a prolonged break) depending on their intensity (i.e., how many posts users produced during sessions), we observe a general decrease in the quality of comments produced by users over the course of sessions. We propose mixed-effects models that capture the impact of session intensity on comments, including their length, quality, and the responses they generate from the community. Our findings suggest performance deterioration: Sessions of increasing intensity are associated with the production of shorter, progressively less complex comments, which receive declining quality scores (as rated by other users), and are less and less engaging (i.e., they attract fewer responses). Our contribution evokes a connection between cognitive and attention dynamics and the usage of online social peer production platforms, specifically the effects of deterioration of user performance.

Suggested Citation

  • Philipp Singer & Emilio Ferrara & Farshad Kooti & Markus Strohmaier & Kristina Lerman, 2016. "Evidence of Online Performance Deterioration in User Sessions on Reddit," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-16, August.
    • Handle: RePEc:plo:pone00:0161636
    DOI: 10.1371/journal.pone.0161636
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    References listed on IDEAS

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    2. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
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    Cited by:

    1. Nathan O. Hodas & Jacob Hunter & Stephen J. Young & Kristina Lerman, 2018. "Model of cognitive dynamics predicts performance on standardized tests," Journal of Computational Social Science, Springer, vol. 1(2), pages 295-312, September.
    2. Prasha Shrestha & Arun Sathanur & Suraj Maharjan & Emily Saldanha & Dustin Arendt & Svitlana Volkova, 2020. "Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-28, March.
    3. Kristina Lerman, 2018. "Computational social scientist beware: Simpson’s paradox in behavioral data," Journal of Computational Social Science, Springer, vol. 1(1), pages 49-58, January.

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