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Research Article Open Access
Social Network have become a very big network where many people are discussing about the hot trends, events and everyday activities which they considered as important with their friends, families and many unknown people. Compare to media like Newspaper, Television the social network is spreading the latest news in a very fast manner and the original talk of the people is spread over the network. The proposed model is to identify the hot topics which is discussed in the social network. The previous methods of finding the hot topics in social network has some limitations like the performance of the model is low, the system detect the topic with high false positive rate. In the proposed model the posts that is shared by the people in social network with their friends by forwarding the posts is considered. The particular post which is forwarded by many people and irregular forwarding nature will be monitored and using change point detection technique and comparing the contents of the posts the perception of hot topic is done.