The Impact of Social Nudges on User-Generated Content for Social Network Platforms

被引:4
|
作者
Zeng, Zhiyu [1 ]
Dai, Hengchen [2 ]
Zhang, Dennis J. [3 ]
Zhang, Heng [4 ]
Zhang, Renyu [5 ]
Xu, Zhiwei
Shen, Zuo-Jun Max [6 ,7 ]
机构
[1] Tsinghua Univ, Dept Ind Engn, Beijing 100000, Peoples R China
[2] Univ Calif Los Angeles, Anderson Sch Management, Los Angeles, CA 90095 USA
[3] Washington Univ St Louis, Olin Business Sch, St Louis, MO 63130 USA
[4] Arizona State Univ, W P Carey Sch Business, Tempe, AZ 85287 USA
[5] Chinese Univ Hong Kong, Dept Decis Sci & Managerial Econ, Hong Kong, Peoples R China
[6] Univ Calif Berkeley, Dept Ind Engn & Operat Res, Berkeley, CA 94720 USA
[7] Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USA
关键词
content production; platform operations; social network; field experiment; information-based intervention; PERFORMANCE FEEDBACK; FIELD EXPERIMENT; SYMBOLIC AWARDS; PRODUCTIVITY; INCENTIVES; WORK; LONG;
D O I
10.1287/mnsc.2022.4622
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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 = 993,676) 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.
引用
收藏
页码:5189 / 5208
页数:21
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