Social Network Analysis Based on the Attention Preference of Weibo College Students
Main Article Content
Abstract
Social networks are characterized by speed, spread, equality and self-organization. With the help of social networks, users can obtain behavioral data based on massive data, which can help operators deeply understand the operation mode of social networks. Since the main active users of the Internet are young people, especially college students, it is of great significance to analyze the social network behavior of college students for the development of online social services in the future. This paper focuses on college students (aged 18-22) in the social platform "Weibo", uses web crawlers and information retrieval to obtain the data of college students' attention relationship and type preference, realizes the visual construction of the data with the help of social network analysis software such as Gephi, summarizes and infers the characteristics and trends of college students' attention preferences after comprehensive research and judgment, and provides help for the operation guidance of the social network platform.
Article Details
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