Abstract:

Articles’ information pushed by academic libraries’ WeChat accounts are collected via the data collection program based on Python language as the sample data in this paper. By employing the theories of Informetrics, such as information statistics, coword analysis, coupling analysis et.al, the amount of WeChat’s articles, average readings, average praises as well as STCI (Single Tweets Communication Index), cosegmentation matrix of article’s title and institution coupling matrix have been obtained and visualized in order to make an easy understanding. Through indepth analysis of these data, this paper reveals the current situation and features of domestic academic libraries WeChat accounts, as well as the rules and problems of pushed articles. The results show that WeChat has become a new promotion tool for domestic academic libraries already. To enhance the promotion performances of WeChat and the quality of pushed articles, all the libraries should focus on the incentive evaluation mechanism, and increase propaganda of the WeChat accounts, improve the quality and interestingness of the WeChat’s articles and the users’ emotional experience.

Key words: Library, WeChat, Data crawling, Informetrics, Cooccurrence analysis, Coupling analysis