Strategic Content Generation and Monetization in Financial Social Media
Ding Li, Khim-Yong Goh, Cheng-Suang Heng
Information Systems Research · 2025 · Volume 36 · Issue 1
Abstract
Financial social media platforms, which rely on social media analysts (SMAs) to contribute content to investors, have emerged as a crucial channel for investors to gain access to financial information and for SMAs to monetize their content. However, we still have a limited understanding of the factors that affect how content is generated and monetized in financial social media platforms. This study focuses on the novel role of investors’ preferences for free/paid content and its sentiment and investigates the extent to which SMAs exhibit strategic content generation and monetization behaviors by catering to and trading off the investors’ preferences. We also evaluate the underlying mechanisms and implications of such strategic behaviors. Utilizing a data set from a financial social media platform based in China, we propose a Bayesian empirical model to jointly analyze the investor’s demand and SMAs’ strategic supply of financial social media content. The model estimation results show that SMAs cater to investors’, especially paid subscribers’, preferences in their content generation such that their strategic behaviors account for 46.20% (24.50%) of the variation in SMAs’ generation decision for free (paid) content sentiment. In addition, an SMA is more likely to produce paid content when the expected free readership increases and is less likely to do so when the expected paid subscriptions increase, evidence that SMAs do balance the preferences of different investors when monetizing content. We find that SMAs are strategic in acquiring readers via their content monetization decisions and retaining subscribers via their content generation decisions. Importantly, we uncover that the orientation of an SMA’s strategic catering behavior is driven by the audience composition effect. Our study provides new empirical evidence, associated theoretical explanations for the results, and a practical illustration of an approach to reduce the potential confirmation bias of investors who may favor information from some SMAs that are prone to strategic catering behaviors. History: Eric Zheng, Senior Editor; Tianshu Sun, Associate Editor. Funding: This research is partially supported by the National Research Foundation, Singapore [Project Grant A-0004920-02-00]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.0482 .
Keywords
strategic behavior, content generation, content monetization, investor preference, financial social media, Bayesian estimation
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