Detecting Topical Opinion Leaders Based on LDA Model in Chinese Microblogs
Daling Wang · Journal of Northeastern University · 2013
How to effectively detect the opinion leaders in the Chinese microblog space has become a hot research problem in the related area.To tackle this issue,an algorithm combined LDA model and HowNet was proposed to classify the short texts in microblogs based on their underlying subtopics.Then an influence measurement containing the criteria on explicit,implicit and user features was introduced.An analytic hierarchy process method was employed to assign different weight of each parameter.Experiment results showed that the proposed short text classification method outperformed the traditional SVM based method,and the proposed influence measurement model could effectively detect the opinion leaders in the Chinese hot topic microblogs.