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Twitter is an interesting platform for the dissemination of news. The real-time nature and brevity of the tweets are conducive to sharing of information related to important events as they unfold. But, one of the greatest challenges is to find the tweets that we can characterize as news in the ocean of tweets. In this paper, we propose a novel method for detecting and tracking breaking news from Twitter in real-time.We filter the stream of incoming tweets to remove junk tweets using a text classification algorithm. Finally, we rank the news using a dynamic scoring system which also allows us to track the news over a period of time.

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How to Cite
A.Jose Prakash, , C.Keerthiraja, P. Kirubhakaran, T. Nithyanandhan, & M. Senthamarai. (2021). Rumour identification in social media using time varying network topology. International Journal of Intellectual Advancements and Research in Engineering Computations, 7(2), 2400–2405. Retrieved from