PTMIB: Profiling top most influential blogger using content based data mining approach

Online Social Network (OSN) provides fastest way to communicate and spread information, influencing users in the network. Blog sites allow the users to reflect and share opinions on various topics of discussion in the form of blogs/online journals and letting readers to comment on their blogs/posts. In this work, a novel method to profile Top Most Influential Blogger (TMIB) is proposed based on content analysis. Contents of blog documents of bloggers under consideration in the blog network are compared and analyzed. Term Frequency and Inverse Document Frequency (TF-IDF) of two blog documents are obtained at a given point of time to get the Cosine Similarity score between those documents. The Influence Scores (IS) of bloggers under conflict are computed. The simulation results demonstrates that the proposed Profiling Top Most Influential Blogger (PTMIB) algorithm is adequately accurate in determining the top most influential blogger at any instant of time considered. © 2016 IEEE