Relational Resonance and Content Creation

内容(测量理论) 计算机科学 业务 知识管理 数学 数学分析
作者
Tingting Song,Yi‐Chun Ho
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
标识
DOI:10.1287/mnsc.2023.00830
摘要

This study investigates how tie formation shapes the production of user-generated content on social media, offering insights into enhancing user engagement and alleviating social media fatigue. We conceptualize tie formation as a relationship codevelopment process involving a tie initiator and a respondent. Drawing on social psychology literature, we propose a framework that traces how initiators’ social cognition evolves throughout this process—from proactively extending an inviting social tie to receiving a responsive one in return. Central to our framework is a perceptual mechanism we term relational resonance, which fosters intrinsic motivation and prompts initiators to adjust their content creation. Using data from YouTube, we develop a Bayesian hierarchical model to identify individual creators’ content adjustments, measured by changes in video volume and viewer engagement. Our results reveal that while initiators tend to reduce content production after receiving a responsive tie, the videos they create generate higher engagement, with “like” and “subscribe” rates increasing by 1.1 and 2.9 percentage points, respectively. Remarkably, the receipt of a responsive tie leads to average weekly increases of 66 likes and 183 subscriptions even after accounting for the decrease in video volume, reinforcing the “quality over quantity” principle in content creation strategies. An online experiment further elucidates the mechanism underlying the observed adjustment behavior, providing robust validation for our proposed framework. Implications for research and practice are discussed. This paper was accepted by D.J. Wu, information systems. Funding: T. Song was supported by National Natural Science Foundation of China [Grants 71902114 and 72372101]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00830 .
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