Purpose: This study aimed to determine if networks of users consistently posting about exercise and fat exist and overlap on social media sites.Method: We collected 3,772,507 posts from Twitter that included the words "fat" and "exercise". Using network structure methods, we identified communities of interconnected users and overlaps between those tweeting "fat" and those tweeting "exercise". Results: Common word pairings were identified using Natural Language Processing (NLP). Networks of

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... consistently talking about exercise (n=3,573) and fat (n=2,007) were found on Twitter. An increased mean total-degree and reduced average path length indicate that the fitness-talk network serves as a connecting bridge between highly scattered communities of the weight-talk network. Conclusion: We identified groups on Twitter dedicated to consistently producing weight stigmatizing content and promoting exercise with weight-loss messages. These groups partially overlap with pro-health groups which could lead to users looking for exercise advice in Twitter to find themselves immersed in a stigmatizing network.