A short summary of the project’s aims:

In the context of digital platform ecosystems, financial social media platforms function as intermediaries, connecting content creators (social media analysts or SMAs) with consumers (investors). These platforms rely on SMAs to generate and monetize content, providing financial insights to investors. However, little is known about the dynamics driving content creation and monetization on these platforms. This study examines how SMAs strategically generate content based on investors’ preferences for free versus paid content and its sentiment. This research employs a Bayesian empirical model to analyze investor demand and SMA content supply on a financial social media platform. Findings show that SMAs adapt their content strategy to meet investor preferences, with strategic behavior explaining 46.20% of the variation in free content and 24.50% in paid content. SMAs also adjust their content monetization approach, increasing paid content when free readership rises but decreasing it when paid subscriptions increase. This study highlights how SMAs balance the interests of different investor groups in their content monetization decisions and strategically acquire and retain their audience. It also reveals that SMAs’ strategic behavior is influenced by the composition of their audience, i.e., free readers and paid subscribers, and offers insights into reducing potential confirmation bias among investors who favor certain SMAs based on this catering behavior. This contributes to our understanding of how digital ecosystems operate, showing that the interaction between content creators and consumers is shaped by both market demand and strategic decisions, influencing the broader platform’s ecosystem.