Research on the application of machine learning in corporate public opinion monitoring and management

This article makes a point of the overall application of corporate public opinion monitoring and management technology based on machine learning. This work proves that by means of case analysis, the basic theories and methods of machine learning, it elaborates on how to use effective machine learning for large-scale public opinion data collection, processing, and analysis, and prediction. Considerable attention is paid to the way natural language processing techniques and sentiment analysis are applied in processing text data and how the models of machine learning, among other support vector machines, decision trees, and neural networks, bear upon implementation in real enterprise environments. Research results show that the level of efficiency and prediction accuracy will be greatly improved if the machine learning technique is applied during public opinion data processing, therefore effectively optimizing the strategy of public opinion response and management of the company. The effectiveness and application scenarios of each prediction model in public opinion analysis were verified through comparative analysis with multiple prediction models, which provided the scientific data support for the decision-making reference of the company.