As we all know that in recent days social media play’s a very prominent role for sharing human social behaviors and participation of multi users in the network. This social media greatly increased the user’s interest in posting various updates of them which happened in and around the world. This social media will also create a facility to study and analyze the general behavior of human to process the large stream of data which is available on the social media database. Till now there are several primitive algorithms that are available in the literature regarding the clustering of user’s interest on social media but they failed to achieve in reducing the time complexity. In this proposed application we for the first time have designed a novel fuzzy c means clustering algorithm for grouping related information of users. By implementing this proposed algorithm and comparing with several primitive algorithms, we can get best group result and also reduce error rate for generating cluster groups

Clustering, Social Media, Fuzzy C Means, Grouping Messages, Time Complexity

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