Clustering of Users on Microblogging Social Media: A Rough Set Based Approach

Microblogging social media platforms like Twitter, Tumblr and Plurk have radically changed our lives. The presence of millions of people has made these platforms a preferred channel for business organizations to target users for product promotions. Clustering of users as per their interest is required to perform the product promotions on these platforms. In this work, we propose a methodology for clustering of users on microblogging social media platforms on the basis of their primitive interest by clustering of micro-messages. We utilize rough set based concept called Similarity Upper Approximation for clustering of micromessages and corresponding users. We demonstrate the viability of the proposed approach by collecting, and clustering tweets and corresponding users from Twitter. Experimental results show that the proposed methodology is viable, and effective for clustering of micro-messages and corresponding users on the basis of their primitive interest.