A Public Psychological Pressure Index for Social Networks

Abstract

With the worldwide proliferation of social networks, public opinion analysis of data generated by social networks has become an important field of research. Social networks have become a major platform for public opinion formation and diffusion, and analyzing public opinion through social network data plays an important role across numerous fields, including political science, economics, commerce, finance, international trade, public policy implementation and so on. Nevertheless, the corresponding quantitative indexes of public opinion analysis have not yet been developed, and the theoretical foundation underpinning such indexes has yet to be established. How to measure public opinion through social network data is a significant problem in need of the development of a series of quantitative assessment indices and social computing methods that can be used to solve this problem. This paper proposes both the concept of a public psychological pressure index and its calculation method, making it a fundamental work in the field of public opinion analysis. The maximum entropy principle is introduced to the social computing domain in this paper and positions it as the theoretical foundation underpinning such indexes.

Keywords

• Information entropy
• intelligence and security informatics
• public information security
• public opinion analysis
• public psychological pressure index
• social computing