A New Method of Identifying Influential Users in the Micro-Blog Networks

Micro-blog services have become popular tools in the social networks. Online users discuss various topics in the micro-blog and some influential users can affect the opinions, attitudes, behaviors, or emotions of others. This paper proposes a user influence rank (UIRank) algorithm to identify the influential users through interaction information flow and interaction relationships among users in the micro-blog. The UIRank algorithm considers the contribution of user's tweet and the characteristics of information dissemination in the micro-blog networks and calculates user influence score iteratively by user follower graph. Experimental results show that the UIRank algorithm outperforms other existing related algorithms in the precision, recall, and F1-Measure value.