The growing importance of social media in financial markets has amplified the role of financial influencers (“finfluencers”) in shaping investor attention and market dynamics. Yet little is known about how finfluencers gain and sustain influence in financial social networks. We conduct this study in the context of meme coin markets, a highly social and sentiment-driven segment of cryptocurrency markets. We examine influence formation in Reddit-based meme coin networks during a full boom–bust cycle (September 2024 to March 2025), using data from 103,882 posts, 609,904 comments, and 128,697 users across ten subreddits.

We model users, posts, comments, subreddits, and hourly market conditions as a heterogeneous graph and apply a Heterogeneous Graph Neural Network (HGNN) to predict user influence rankings. The HGNN framework allows us to jointly incorporate topological structure, content features, user attributes, and market states without manually specifying interaction patterns.

Our results show that influence mechanisms are strongly market-state dependent. During high-volatility periods, network position and engagement timing dominate, while content features lose predictive power. In contrast, content quality becomes important in stable markets. We further identify a highly skewed hierarchy of influence and distinguish sustained finfluencers from occasional ones, with persistence driven by consistent activity and central network positioning.