Micro-Blog Influence Evaluation Method Based on Particle Swarm Optimization Algorithm

Micro-blog is regarded as one of the most popular platforms for information sharing based on Web 2.0 technology. In this paper, we propose a novel Micro-blog influence evaluation method by modeling users' behaviors in Micro-blog platform. Firstly, considering the Micro-blog API data capture method program is simple, we aim to achieve a higher efficiency and consistency of data crawling by relieving the API access frequency limit. Secondly, inspired by the fact that a follower who has higher influence can effectively spread his tweets than the one with lower influence, we propose a particle swarm optimization based Micro-blog influence evaluation method. Finally, experimental results demonstrate that the proposed PSO based algorithm is able to estimate the Micro-blog user influence with high accuracy.