Like the Facebook, the Twitter and the TikTok, the WeChat is a well-known mobile instant messaging product with over 1 billion active accounts, and it supports text messages, voices, videos, pictures and payments. The Ministry of Science and Technology of the People's Republic of China makes the science and technology management through various social media, including the WeChat, and the "Rui Ke Ji(Sharp S&T)" is the official WeChat account of the Ministry of Science and Technology, providing information for scientists and technicians. Unlike the editing of the traditional science and technology newspapers and periodicals, the WeChat official account "Rui Ke Ji" has its own characteristics in the manuscript selection and publication (push). In order to see the coverage of the topics of the WeChat articles changing over the time and the relationship between the topics of the articles and the view accounts, a Bias probability topic model, AToT, is used to quantitatively analyze and mine the contents of the articles in the "Rui Ke Ji" and its sub account the "Rui dong yuan(Sharp Dynamic Source)" in this paper. The results reveal where the ministry's publicity lies and how the topics of the articles change over the time. The reading preferences of Chinese scientists and technicians are analyzed and it is shown that there is a certain relationship between the contents of the WeChat articles and the page views. This study helps to improve the editing level of the new media and the science and technology publicity.
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