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- W4292231752 abstract "The lives of people have been affected massively with the entrance of web and internet-based life. In addition general public life is affected by mass-media. These privileges are exploited by many people due to political influence, for luxuries, increasing their social status. Covid-19 pandemic is one example where the people aren’t completely aware of daily cases due to the spread of fake feed. People use web-based social networking platforms to disseminate these counterfeit items on purpose. This affects the original functioning and intent of online news sites. So in order to curb such malicious news from being spread we need some tools to automate the process and find efficient ways to classify it. The major goal of this study is to develop a reliable and accurate model that uses ML algorithms and NLP techniques to classify a given news article as false or genuine, allowing only authentic news to be presented to the public." @default.
- W4292231752 created "2022-08-19" @default.
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- W4292231752 date "2022-04-27" @default.
- W4292231752 modified "2023-09-26" @default.
- W4292231752 title "News Classification using Natural Language Processing" @default.
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- W4292231752 doi "https://doi.org/10.1109/iciem54221.2022.9853174" @default.
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