Analysis of the Evolution of Police-Related Public Opinion Based on Multi-Source Online Public Opinion Big Data

Police-Related Public Opinion, with its rapid spread and wide impact, has become a major challenge for public security work in the new era. In response, this paper conducts a study on the evolution mechanism of police-related public opinion based on multi-source online public opinion big data. First, the core concepts of police-related public opinion are outlined, clarifying the role of multiple actors and the stages of evolution. Then, positive information spreaders, negative information spreaders, and informers are introduced to construct the SPNIR model for the evolution of police-related public opinion. An empirical analysis was conducted using a local police-related case to verify the accuracy and effectiveness of the model. Finally, the study examines the impact of the intervention time and number of informers on the evolution of public opinion, finding that reasonable intervention strategies can effectively control the spread of negative information. This research provides a new theoretical framework and methodological support for an in-depth exploration of the evolution patterns of police-related public opinion.