Analysis of microblog users influence based on the social network model

Abstract

With the development of science and technology in today's world, social software and networks have become more and more advanced. Microblog is a widely used application and everyone in China has to contact it. According to calculations, thousands of microblogs can be generated every second, so the impact of microblogs is huge. At present, the research on microblogging social networks is relatively few, and the research on user influence in microblogging is even less. Even if the influence of users in microblogs is studied, the methods used are relatively complex, and it is impossible to simply and clearly select users with greater influence. Therefore, based on the social network model, this paper first uses a Web crawler to obtain microblog data. This paper obtains only one user's id, gender, age, city, number of followers, number of posts, attitudes, and comments. When this paper gets the data, this paper uses the knowledge of graph theory to simplify the specific data, so as to better study the relationship between the data and explore their influence. This paper regards every user in microblog as a node, and the relationship between the users is the edges. Then calculate each nodes Degree Centrality and Eigenvector Centrality to find influential users. This paper finds that the influence gap between different users is large. Women's influence is slightly higher than men's. The youth group is significantly larger than that of the others. The influence of first tier cities and new first tier cities is slightly higher than those of second tier cities, and their influence is significantly higher than those of other cities. These results will help people suit the remedy to the case and achieve better communication results.