The impact of social nudges on user-generated content for social network platforms
Open accessAbstract
Content-sharing social network platforms rely heavily on user-generated content to attract users and advertisers, but they have limited authority over content provision. We develop an intervention that leverages social interactions between users to stimulate content production. We study social nudges, whereby users connected with a content provider on a platform encourage that provider to supply more content. We conducted a randomized field experiment (N [Formula: see text]) on a video-sharing social network platform where treatment providers could receive messages from other users encouraging them to produce more, but control providers could not. We find that social nudges not only immediately boosted video supply by 13.21% without changing video quality but also, increased the number of nudges providers sent to others by 15.57%. Such production-boosting and diffusion effects, although declining over time, lasted beyond the day of receiving nudges and were amplified when nudge senders and recipients had stronger ties. We replicate these results in a second experiment. To estimate the overall production boost over the entire network and guide platforms to utilize social nudges, we combine the experimental data with a social network model that captures the diffusion and over-time effects of social nudges. We showcase the importance of considering the network effects when estimating the impact of social nudges and optimizing platform operations regarding social nudges. Our research highlights the value of leveraging co-user influence for platforms and provides guidance for future research to incorporate the diffusion of an intervention into the estimation of its impacts within a social network. This paper was accepted by Victor Martínez-de-Albéniz, operations management. Funding: H. Dai thanks the University of California, Los Angeles (UCLA) [Hellman Fellowship and Faculty Development Award] for funding support. R. Zhang is grateful for financial support from the Hong Kong Research Grants Council [Grant 16505418]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4622 .
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From What Influences Users’ Intention to Share Works in Designer-Driven User-Generated Content Communities? A Study Based on Self-Determination Theory (2023) · cites this paper as [56]
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Ryan, R. M., & Deci, E. L. (2000) · American Psychologist · doi:10.1037//0003-066x.55.1.68 · Cited by 27,815 · see citing works
A little thanks goes a long way: explaining why gratitude expressions motivate prosocial behavior
Grant, A. M., & Gino, F. (2010) · Journal of Personality and Social Psychology · doi:10.1037/a0017935 · Cited by 870 · see citing works
Bapna, R., & Umyarov, A. (2015) · Management Science · doi:10.1287/mnsc.2014.2081 · Cited by 350 · see citing works
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Song, H., Wei, J., & Jiang, Q. (2023) · Systems · doi:10.3390/systems11110540 · Cited by 13 · see citing works
- Authors
- Zeng, Z., Dai, H., Zhang, D. J., Zhang, H., Zhang, R., Xu, Z., & Shen, Z.-J. M.
- Affiliations
- Tsinghua University (CN)
- University of California, Los Angeles (US)
- Washington University in St. Louis (US)
- Arizona State University (US)
- Chinese University of Hong Kong (HK)
- Independent Contributor, Beijing 100000, China;
- University of California, Berkeley (US)
- Venue
- Management Science
- Published
- 2023-09
- Volume
- 69
- Issue
- 9
- Pages
- 5189-5208
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W4312001262
- Cited by
- 76
- References
- 3
- Citations by year
- 2026: 19 · 2025: 29 · 2024: 17 · 2023: 6 · 2022: 3 · 2021: 1 · 2020: 1
- FWCI
- 3.42
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Management Science (publishedVersion)
- SSRN Electronic Journal (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
- Keywords
- social nudges, user-generated content, content creation, online video platforms, social network models, network effects, platform operation
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