The study of micro-blog information diffusion model based on community structure detection

As social network services become more popular and many commercial groups use micro blog as a media for information distribution, the analysis of the community structure in online social network specially the identification of significant nodes in information distribution is very important. In this paper the author investigates an algorithm that use the multi-dimension attributes of micro-blog user and the multiple iterations thought of page-rank to discover the center node of the community, and integrate multi-path to calculate the information diffusion distance from the center node to every node in the network, finally discover the communities in the network and construct the information diffusion model in a tree data structure. The algorithm is validated by applying it to a 16769 nodes dataset climbed from sina micro-blog user network and the result is as expected.