Technology for mining social network data based on natural language processing

The vigorous development of social networks has given rise to massive amounts of unstructured text data. How to efficiently extract valuable information from it has become a research focus. This paper focuses on the application of natural language processing technology in social network data mining and constructs a complete technical framework. Firstly, it analyzes the structure of the data mining system, covering the links of data acquisition, storage, processing, and mining analysis. Then, it deeply explores Chinese word segmentation algorithms, model training methods, and data mining technology based on the SVM model, and improves the accuracy of technical elaboration by introducing relevant formulas. The research provides a technical reference for in-depth mining of social network data and helps to effectively extract information such as user behavior and emotional tendencies.