Social Media User Behavior Mining and Sentiment Analysis based on Computer Big Data

Faced with the rapid development of social networks and the enormous business opportunities they contain, data mining and analysis based on social networks has become an inevitable trend. By utilizing various technologies such as Visual C++6.0 and Pajek, data collection and analysis were achieved. The user ID (Identification) was added to the Sina server and relevant user information was requested through the API (Application Programming Interface). Through the data analysis module, the stored data was processed appropriately for different research objects, and network analysis tools can be used to visually display certain results. Using this model, sentiment classification was performed on Weibo samples with existing labels, and the accuracy, recall and F1 value of manual labeling were evaluated. The positive accuracy was 0.85; recall was 0.82; F1 value was 0.84. This article helps to improve user experience and explore more user value.