The Effects of Social Media Content Created by Human Brands on Engagement: Evidence from Indian General Election 2014

• 成果类型: Article
• 署名作者: Mallipeddi, Rakesh R.; Janakiraman, Ramkumar; Kumar, Subodha; Gupta, Seema
• 署名单位: Tulane University; University of South Carolina System; University of South Carolina Columbia; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; Indian Institute of Management (IIM System); Indian Institute of Management Bangalore
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2020.0961
• 发表日期: 2021
• 页码: 212-237
• 关键词: spreading activation theory; Word-of-mouth; reviews; IMPACT; identification; perception; BEHAVIOR; sales; talk

摘要

Individual celebrities or human brands in fields ranging from sports to art to politics use social media platforms to connect and engage with their audience. We analyze the effects of content generated by human brands (referred to as human brand generated content) on a popular social media platform, Twitter, on audience engagement. The first objective of this study is to examine the effects of positive and negative tone of human generated content on social media engagement. Next, we study the impact of popularity of human brands on the effect of tone on audience's engagement. Building on the arguments of perception spillover effects, we also investigate the effects of content generated by related human brands on the engagement of the focal human brand. Set in the context of the 2014 Indian general election, we find that both positive-toned content and negative-toned content have a positive effect on social media engagement. We find that the popularity of a human brand negatively moderates the relationship between positive-toned content and engagement. Our findings indicate interesting spillover effects of content created by related brands on the effectiveness of content created by a focal human brand. In particular, we find evidence for presence of the reinforcement effect, that is, the effect of negative tone on engagement is greater when the tone of related human brands is negative and the engagement is higher when the tones of both the focal human brand and related brands are positive. However, we find that the effect of negative-toned tweets of a focal human brand is lower when the tone of related human brands is positive. Our analyses account for endogeneity issues, correlated unobservables, and reflection problem. We supplement our core results with additional analyses that include alternative model specifications, alternative samples, estimation strategies, and engagement metrics. We present implications of this study to practice and the literature on social media content.