Financial Data Mining and Performance Evaluation of Convergent Media from the Perspective of Social Responsibility

Abstract

Enterprise financial performance is one of the most concerned problems of many stakeholders, and the evaluation results will be reflected in the capital market to a large extent. In this paper, data mining technology is used to analyze the psychological and behavioral characteristics of investors. Decision tree C5.0 algorithm and BP neural network algorithm are used to study the financial indicators and decision-making mode that investors focus on when analyzing the annual financial statements of convergent media industry. This paper establishes decision tree evaluation model and BP neural network evaluation model to provide auxiliary tools for investors to evaluate the financial performance of convergent media technology enterprises and make scientific investment decisions. The empirical study shows that the two models have strong prediction ability, which verifies the accuracy of using data mining technology to simulate the financial performance evaluation model.