TY - GEN
T1 - Social Media Moderations, User Ban, and Content Generation
T2 - 55th Annual Hawaii International Conference on System Sciences, HICSS 2022
AU - Zhang, Xiaohui
AU - Wei, Zaiyan
AU - Du, Qianzhou
AU - Zhang, Zhongju
N1 - Publisher Copyright:
© 2022 IEEE Computer Society. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Social media platforms have evolved as major outlets for many entities to distribute and consume information. The content on social media sites, however, are often considered inaccurate, misleading, or even harmful. To deal with such challenges, the platforms have developed rules and guidelines to moderate and regulate the content on their sites. In this study, we explore user banning as a moderation strategy that restricts, suspends, or bans a user who the platform deems as violating community rules from further participation on the platform for a predetermined period of time. We examine the impact of such moderation strategy using data from a major Q&A platform. Our analyses indicate that user banning increases a user's contribution after the platform lifts the ban. The magnitude of the impact, however, depends on the user's engagement level with the platform. We find that the increase in contributions is smaller for a more engaged user. Additionally, we find that the quality of the user-generated content (UGC) decreases after the user ban is lifted. Our research is among the first to empirically evaluate the effectiveness of platform moderations. The findings have important implications for platform owners in managing the content on their sites.
AB - Social media platforms have evolved as major outlets for many entities to distribute and consume information. The content on social media sites, however, are often considered inaccurate, misleading, or even harmful. To deal with such challenges, the platforms have developed rules and guidelines to moderate and regulate the content on their sites. In this study, we explore user banning as a moderation strategy that restricts, suspends, or bans a user who the platform deems as violating community rules from further participation on the platform for a predetermined period of time. We examine the impact of such moderation strategy using data from a major Q&A platform. Our analyses indicate that user banning increases a user's contribution after the platform lifts the ban. The magnitude of the impact, however, depends on the user's engagement level with the platform. We find that the increase in contributions is smaller for a more engaged user. Additionally, we find that the quality of the user-generated content (UGC) decreases after the user ban is lifted. Our research is among the first to empirically evaluate the effectiveness of platform moderations. The findings have important implications for platform owners in managing the content on their sites.
UR - http://www.scopus.com/inward/record.url?scp=85152241883&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85152241883&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85152241883
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 4432
EP - 4441
BT - Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022
A2 - Bui, Tung X.
PB - IEEE Computer Society
Y2 - 3 January 2022 through 7 January 2022
ER -