Interactive Behavior Analysis Based on Social Network

To make rational use of the behavior data generated in the process of online teaching, this paper adopts social network analysis technology to conduct in-depth research on the interactive behavior. Based on the behavior data obtained from online teaching space, we analyze the characteristics of interaction through the basic attributes, centrality and density of the network and social network is used to analyze the interactive network structure formed by online discussion. Combined with content, behavior sequence and other methods, UCINET is used for visual analysis and output to find out the main factors that affect interaction behavior and the tendency of learners to choose interaction objects. The experimental results show that the scheme can acquire the influence degree of members' attributes on interaction frequency, and take corresponding measures to promote the formation of a more reasonable social network.