Identifying Chronic Disease Themes Research on Social Networks Based on Artificial intelligence and Big Data

With the rapid advancement of technology, social networks have gradually evolved into a core platform for people to exchange health insights and share health information. Chronic diseases, as one of the most prevalent health challenges, have a significant negative impact on individuals' quality of life and physical and mental health. In this context, social networks have become a crucial channel for chronic disease patients to access valuable health information. To more effectively tap into and utilize the vast amount of health information resources generated by users on the internet, this paper conduct in-depth exploration and identification of chronic disease themes in the context of social networks. This paper selects four chronic disease texts of diabetes, hypertension, depression and autism in social networks as objects, and conducts research on themes and emotions through network text mining. an LDA-based topic model was constructed to conduct topic analysis on four chronic disease data, and social support theory was introduced on this basis. Finally, Sentistrength was used to perform sentiment computation on tweets of four chronic diseases, and SPSS was used to analyze the differences in sentiment among different diseases and social support topics. system.