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The Never Ending Book: The role of external stimuli and peer feedback in user-generated content production

Author

Listed:
  • Maria Marchenko

    (Department of Economics, Vienna University of Economics and Business)

  • Hendrik Sonnabend

    (Department of Economics and Business Administration, University of Hagen)

Abstract

This paper studies the determinants of the voluntary provision of user-generated (online) content. Using data from the largest fanfiction website, we find that writers respond differently to new original material: conditional on text length, writing times increase for the average writer and even more for the elite of prolific writer. We explain this finding with quality concerns. In addition, we find supportive evidence that community feedback encourages first-time contributors to continue publishing. For more established writers, we find that community feedback has a rather dampening effect on text lengths and writing times. Overall, these effects are more pronounced for high-quality community feedback ('reviews') compared to low-quality community feedback ('following', 'favoriting').

Suggested Citation

  • Maria Marchenko & Hendrik Sonnabend, 2022. "The Never Ending Book: The role of external stimuli and peer feedback in user-generated content production," Department of Economics Working Papers wuwp320, Vienna University of Economics and Business, Department of Economics.
    • Handle: RePEc:wiw:wiwwuw:wuwp320
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    1. Kathryn Graddy & Carl Lieberman, 2018. "Death, Bereavement, and Creativity," Management Science, INFORMS, vol. 64(10), pages 4505-4514, October.
    2. Luís Cabral & Lingfang (Ivy) Li, 2015. "A Dollar for Your Thoughts: Feedback-Conditional Rebates on eBay," Management Science, INFORMS, vol. 61(9), pages 2052-2063, September.
    3. Scott K. Shriver & Harikesh S. Nair & Reto Hofstetter, 2013. "Social Ties and User-Generated Content: Evidence from an Online Social Network," Management Science, INFORMS, vol. 59(6), pages 1425-1443, June.
    4. Maria Marchenko, 2020. "Peer effects in art prices," Department of Economics Working Papers wuwp298, Vienna University of Economics and Business, Department of Economics.
    5. Daniel P. Gross, 2020. "Creativity Under Fire: The Effects of Competition on Creative Production," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 583-599, July.
    6. Borowiecki, Karol Jan, 2013. "Geographic clustering and productivity: An instrumental variable approach for classical composers," Journal of Urban Economics, Elsevier, vol. 73(1), pages 94-110.
    7. Gordon Burtch & Yili Hong & Ravi Bapna & Vladas Griskevicius, 2018. "Stimulating Online Reviews by Combining Financial Incentives and Social Norms," Management Science, INFORMS, vol. 64(5), pages 2065-2082, May.
    8. Warut Khern-am-nuai & Karthik Kannan & Hossein Ghasemkhani, 2018. "Extrinsic versus Intrinsic Rewards for Contributing Reviews in an Online Platform," Information Systems Research, INFORMS, vol. 29(4), pages 871-892, December.
    9. DeVaro, Jed & Kim, Jin-Hyuk & Wagman, Liad & Wolff, Ran, 2018. "Motivation and performance of user-contributors: Evidence from a CQA forum," Information Economics and Policy, Elsevier, vol. 42(C), pages 56-65.
    10. Aleksi Aaltonen & Stephan Seiler, 2016. "Cumulative Growth in User-Generated Content Production: Evidence from Wikipedia," Management Science, INFORMS, vol. 62(7), pages 2054-2069, July.
    11. Yan Chen & F. Maxwell Harper & Joseph Konstan & Sherry Xin Li, 2010. "Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens," American Economic Review, American Economic Association, vol. 100(4), pages 1358-1398, September.
    12. Olivier Toubia & Andrew T. Stephen, 2013. "Intrinsic vs. Image-Related Utility in Social Media: Why Do People Contribute Content to Twitter?," Marketing Science, INFORMS, vol. 32(3), pages 368-392, May.
    13. Paulo B. Goes & Chenhui Guo & Mingfeng Lin, 2016. "Do Incentive Hierarchies Induce User Effort? Evidence from an Online Knowledge Exchange," Information Systems Research, INFORMS, vol. 27(3), pages 497-516, September.
    14. Monic Sun & Feng Zhu, 2013. "Ad Revenue and Content Commercialization: Evidence from Blogs," Management Science, INFORMS, vol. 59(10), pages 2314-2331, October.
    15. Jana Gallus, 2017. "Fostering Public Good Contributions with Symbolic Awards: A Large-Scale Natural Field Experiment at Wikipedia," Management Science, INFORMS, vol. 63(12), pages 3999-4015, December.
    16. Ni Huang & Gordon Burtch & Bin Gu & Yili Hong & Chen Liang & Kanliang Wang & Dongpu Fu & Bo Yang, 2019. "Motivating User-Generated Content with Performance Feedback: Evidence from Randomized Field Experiments," Management Science, INFORMS, vol. 65(1), pages 327-345, January.
    17. Xiaoquan (Michael) Zhang & Feng Zhu, 2011. "Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia," American Economic Review, American Economic Association, vol. 101(4), pages 1601-1615, June.
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    More about this item

    Keywords

    fanfiction; user-generated content; online public goods; voluntary contribution;
    All these keywords.

    JEL classification:

    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature

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