Analyzing behavior of the social media users through swarm intelligence perspective

Swarm intelligence is defined as the properties of artificial systems. It is suited to depict people's daily behavior, such as social media users' behavior. Social media users have some characteristics. For one thing, users who have the same interest will focus on the same VIP (Very Important Person) users inside the industry. For another, the users concentrating on the same VIP user may focus on each other. It is formed by common interests as the cluster center. Based on the characteristics, we analyse the Sina Weibo as the research object. From the perspective of swarm intelligence, the multi-agent mechanism model has been established. In this paper, we implemented the user behavior model and studied the following aspects. Firstly, we clarify how the same interests can lead to the clustering of the users, and what the path of the clustering evolution would be. Secondly, we measure the influence of VIP users in the industry. In order to solve the above problems, we use the computational experiment method to simulate clustering process via the K-PSO algorithm (K-Particle Swarm Optimization). We select the RePast as the simulation experiment tool. The simulation results are highly consistent with the expected experimental results.

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