MICROBLOGGING REPLIES AND OPINION POLARIZATION: A NATURAL EXPERIMENT

• 成果类型: Article
• 署名作者: Lu, Yingda; Wu, Junjie; Tan, Yong; Chen, Jian
• 署名单位: University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Beihang University; University of Washington; University of Washington Seattle; Tsinghua University
• 刊物名称: MIS QUARTERLY
• ISSN/ISSBN: 0276-7783
• DOI: 10.25300/MISQ/2022/15455
• 发表日期: 2022
• 页码: 1901-1936
• 关键词: word-of-mouth; social networks; media bias; Confirmation bias; user reviews; internet use; online; ratings; involvement; DYNAMICS

摘要

In recent years, there has been a heated discussion on opinion polarization on social media platforms. Extant research attributes the emergence of echo chambers to higher exposure to information from users' existing social networks, which consists of like-minded others and argues that the provision of information from outside users' networks could alleviate opinion polarization. In this paper, we formulate a hierarchical Bayesian learning model to investigate the impact of replies, one of the main channels for information outside of users' networks, on opinion polarization. We leverage a unique natural experiment contained in the data from a leading microblogging website in China in which the reply function was shut down for three days. This setting allows us to identify the impact of replies from that of peer microblogs. We found that shutting down reply function reduced sentiment polarization on the microblogging site. In addition, this effect was more significant for individuals with higher social media participation. The results of this study shed light on marketing campaign strategies as well as the ways in which platform design can reduce polarization.