Volume : 4, Issue : 4, MAR 2020


Manikandan V, Rajkumar S


Twitter may be a stimulating platform for the dissemination of stories. The real-time nature and brevity of the tweets are conducive to sharing of knowledge related to important events as they unfold. But, one of the simplest challenges is to hunt out the tweets that characterize as news within the ocean of tweets. The paper propose a totally unique method for detecting and tracking breaking news from Twitter in real-time. Filtering the stream of incoming tweets to urge obviate junk tweets employing a text classification algorithm and also compare the performance of varied supervised SVM text classification algorithms for this task. After classification then cluster similar tweets, so that, tweets within the same cluster relate to an equivalent real-life event and should be termed as a breaking news. Finally, rank the news employing a dynamic scoring system which also allows us to trace the news over a period of some time.


SVM, Twitter.

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