Evaluating User Influence Based on the Properties of User in Social Networks

In large-scale social networks, identifying the most influential collection of nodes plays an important role in recommendation, public opinion analysis and product marketing. Therefore, identifying the collection of nodes which have the most influence by evaluating the user influence is an important research direction. The paper analyzes and studies an algorithm for evaluating the nodes influence, and presents the improvement methods based on the PageRank algorithm, and identifies that the improvement methods are better than the PageRank algorithm.