Research on False Public Opinion Recognition Method of Social Network Based on Fuzzy Cluster Analysis

In order to solve the problem that the classification of network pseudo public opinion events is too subjective, a social network pseudo public opinion recognition method based on fuzzy cluster analysis is proposed. Combined with the principle of fuzzy cluster analysis, a newindex system for identifying false and emotional events is established. On this basis, the relevant index data of network false and emotional events are collected, and the classical fuzzy cluster analysis algorithm is used to cluster and analyze the network false and emotional events, so as to obtain different types of network false and emotional event sets, analyze and summarize the characteristics of all kinds of false and emotional events, and finally confirm through experiments, The social network false public opinion identification method based on fuzzy cluster analysis has high practicability, provides a new method for the identification and classification of network false and sentiment, and provides a reference for relevant departments to accurately control all kinds of false and sentiment by using network big data.