Improved spam detection in social network using machine learning

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dc.contributor.authorAthavani, Shahin
dc.contributor.authorShaikh, Owais (17DET36)
dc.contributor.authorShaikh, Arshinaaz (17DET61)
dc.contributor.authorKazi, Adil (17DET41)
dc.date.accessioned2021-11-09T06:56:21Z
dc.date.available2021-11-09T06:56:21Z
dc.date.issued2020-05
dc.description.abstractThe large use of social media has tremendous impact on our society, culture, business with potentially positive and negative effects. Now-a-days, due to the increase in use of online social networks, the fake news for various commercial and political purposes has been emerging in large numbers and widely spread in the online world. The existing systems are not efficient in giving a precise statistical rating for any given news. Also, the restrictions on input and category of news make it less varied. This paper develops a method for automating fake news detection for various events. We are building a classifier that can predict whether a piece of news is fake based on data sources, thereby approaching the problem from a purely NLP perspective.en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3628
dc.language.isoenen_US
dc.publisherAIKTCen_US
dc.subjectProject Report - EXTCen_US
dc.titleImproved spam detection in social network using machine learningen_US
dc.typeOtheren_US
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