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Cumulative Growth in User-Generated Content Production: Evidence from Wikipedia

Author

Listed:
  • Aleksi Aaltonen

    (Warwick Business School, University of Warwick, Coventry CV4 7AL, United Kingdom)

  • Stephan Seiler

    (Stanford Graduate School of Business, Stanford University, Stanford, California 94305)

Abstract

Open content production platforms typically allow users to gradually create content and react to previous contributions. Using detailed edit-level data across a large number of Wikipedia articles, we investigate how past edits shape current editing activity. We find that cumulative past contributions, embodied by the current article length, lead to significantly more editing activity, while controlling for a host of factors such as popularity of the topic and platform-level growth trends. The magnitude of the effect is large; content growth over an eight-year period would have been 45% lower in its absence. Our findings suggest that other open content production environments are likely to also benefit from similar cumulative growth effects. In the presence of such effects, managerial interventions that increase content are amplified because they trigger further contributions.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2015.2253 . This paper was accepted by Pradeep Chintagunta, marketing .

Suggested Citation

  • 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.
    • Handle: RePEc:inm:ormnsc:v:62:y:2016:i:7:p:2054-2069
    DOI: 10.1287/mnsc.2015.2253
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    References listed on IDEAS

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    1. Spiliopoulos, K. & Sofianopoulou, S., 2007. "Calculating distances for dissimilar strings: The shortest path formulation revisited," European Journal of Operational Research, Elsevier, vol. 177(1), pages 525-539, February.
    2. Kummer, Michael E., 2013. "Spillovers in networks of user generated content: Evidence from 23 natural experiments on Wikipedia," ZEW Discussion Papers 13-098, ZEW - Leibniz Centre for European Economic Research.
    3. 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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    Cited by:

    1. Li, Dongkun & Chen, Yufeng & Miao, Jiafeng, 2022. "Does ICT create a new driving force for manufacturing?—Evidence from Chinese manufacturing firms," Telecommunications Policy, Elsevier, vol. 46(1).
    2. Stephan Seiler & Song Yao & Wenbo Wang, 2017. "Does Online Word of Mouth Increase Demand? (And How?) Evidence from a Natural Experiment," Marketing Science, INFORMS, vol. 36(6), pages 838-861, November.
    3. Barbosu, Sandra & Gans, Joshua S., 2022. "Storm crowds: Evidence from Zooniverse on crowd contribution design," Research Policy, Elsevier, vol. 51(1).
    4. Marchenko, Maria & Sonnabend, Hendrik, 2022. "The Never Ending Book: The role of external stimuli and peer feedback in user-generated content production," Department of Economics Working Paper Series 320, WU Vienna University of Economics and Business.
    5. Marit Hinnosaar & Toomas Hinnosaar & Michael E. Kummer & Olga Slivko, 2022. "Externalities in knowledge production: evidence from a randomized field experiment," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 706-733, April.
    6. Kai Zhu & Dylan Walker & Lev Muchnik, 2020. "Content Growth and Attention Contagion in Information Networks: Addressing Information Poverty on Wikipedia," Information Systems Research, INFORMS, vol. 31(2), pages 491-509, June.

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