Opinion Leader Mining Algorithm in Microblog Platform Based on Topic Similarity

摘要

The study of opinion leader mining is an important research subject of social network, especially in public opinion monitoring, network marketing and other aspects of great significance. Currently opinion leader mining in microblog usually just considers the user attributes, network structure and interactive features, but the characteristic of microblog topic is considered less. However, opinion leaders tend to have domain restriction which they have greater influence on particularly certain topic areas but weak in other areas. To solve this problem, we propose TopicSimilarRank algorithm based on interactive information and similarity of topics, which can be called TSR algorithm in short. The algorithm considers user attributions and text characteristic in microblog, building links between the users based on user interaction informations that combine with topic similarity to construct a directed-weighted network, then considering the idea of vote in PageRank algorithm to mine opinion leaders. We select Sina Weibo data sets to our experiment, the result shows that our algorithm has a better performance.