Text and Data Mining of Social Media in Science and Technology Publicity

Abstract

WeChat is a new generation of mobile instant messaging product, which has over 800 million active accounts and support voice, video, pictures and text messages. China's Ministry of Science and Technology has applied social media to science and technology management. Rui Dong Ruan is one of the official accounts in the WeChat matrix of China's Ministry of Science and Technology. This research proposes an approach which uses Chinese word segmentation and topic model to processing texts of Rui Dong Ruan. The experimental result shows that there is a certain relationship between the content of the articles and the view counts on WeChat, which can make the science and technology publicity more efficient and effective.