关键词: 网络舆情, 政务微博, PageRank, 社会网络分析, GM-Rank

Abstract: With the rise and popularization of the Internet, social media platforms such as Weibo have become more and more influential in human society. Government microblog is an official account opened by government departments on the microblog platform. It is an important part of the social media platform and an important channel for official communication and guidance of public opinion. It is usually used to publicize government information, respond to public opinion, and promote government achievements. The influence of government micro-blog is the most important measurement index for government departments to carry out policy propaganda and smooth communication between government and people, and selecting the appropriate method to evaluate the influence is the key work for the government to carry out the new media management of government affairs.
The existing work of microblog influence evaluation generally has three modes, based on the basic attributes of users, interactive behavior and social network structure. However, these algorithms usually have some problems such as incomplete index selection, static analysis mode, and single social network construction mode. Therefore, according to the reality of government microblog in social network platform, this paper carries out the influence evaluation of government microblog based on interaction behavior analysis and social network theory. Firstly, we use the Selenium module for the web reptile to obtain the basic information and interaction behavior information of 4492 government microblogs, and the Chinese government microblog data set is constructed. Then, by analyzing the main interactive behavior patterns of microblog (including the interaction between government microblogs, the interaction between government microblogs and ordinary users, and the user recommendation mechanism), the multi-dimensional social network system of government microblogs is constructed according to the mention, forwarding behavior and user recommendation relationship. Secondly, aiming at the defects of the traditional PageRank algorithm, this paper improves an influence evaluation algorithm GM-Rank which is more suitable to government microblog. GM-Rank takes the normalized number of fans and the number of microblogs as the initial PR value, and carries out unequal PR value propagation according to the correlation tightness of microblogs, and iteratively calculates the influence of government microblogs. Finally, the government microblog is ranked and the social network form and development situation of the domestic mainstream government new media are analyzed.
The experimental results show that, compared with the existing microblog influence evaluation algorithm, the GM-Rank method is practical and available, which can intuitively and effectively reflect the influence and development status of government microblog, and also provide a reliable reference for government departments to carry out the evaluation and management of government affairs new media.
Based on the experimental results, this paper analyzes the development status and characteristics of Chinese government microblog, and puts forward three policy suggestions: paying attention to the construction of internal matrix, improving the multi-level system of departments, and strengthening the cooperation and exchange between microblogs. In the next research, we will consider realizing the automation of the whole process through the encapsulation program, in order to serve the construction and development of government microblog more conveniently.

Key words: network public opinion, government microblog, PageRank;social networks, GM-Rank