Research on Emotion Analysis Based on a Topic Emotion Fusion Model: The Case of the "Post-holiday Symptoms of Pharyngitis" Event on the Weibo Platform

[Objective] From early 2023 to 2024, multiple public health incidents related to "post-holiday pharyngitis" erupted in china, impacting public health and education among other areas. This study analyzes the data dissemination trends and the emotional development of these incidents. The insights are aimed at enhancing the government and disease control agencies' mechanisms for guiding and responding to such public sentiment incidents, thereby improving preparedness and response capabilities for potential future public health events. [Methods] The methodology employed involves using three instances of "post-holiday pharyngitis" events on the Weibo platform as data samples. The study applies the LDA model integrated with TD-IDF weighted Word2vec algorithm for thematic organization across different periods. The DUTIR sentiment dictionary is used to analyze public sentiment, and data visualization techniques are employed to present the thematic-emotional evolution within the incidents. [Results] The results suggest that the proposed thematic-emotional fusion model effectively extracts and analyzes the dissemination trends and emotional evolution of the event, providing actionable suggestions for government and public health agencies in managing such public sentiment incidents.