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In identifying the trustworthy information in the presence of noisy data contributed by numerous unvented sources from online social media (e.g., Twitter, Facebook, and Instagram) has been a crucial task in the era of big data. In the proposed system, we develop a Scalable and Robust Truth Discovery (SRTD) scheme to address the above three challenges. In particular, the SRTD scheme jointly quantifies both the reliability of sources and the credibility of claims using a principled approach. In this Phase, we implement removal of Vulgar words while
posting the data in the social media. We also analyze the people frustration,  agitation and protest content posted by the public in the social media. This is much more helpful for unwanted or criminal data input in the social media.

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