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- W4312907753 abstract "Social Media is very popular now a days to share news, communicate and discuss about trending topics. As we are aware whenever there is a positive promotion, there will be surely a negative part associated with it. Such a negative part in social media is the travel of fake contents in the news that are travelled in a very fast manner than the true content. Hence it is necessary to develop a methodology to detect the fake contents that are propagating in social media. In our work we have used the Recurrent Neural Network to detect the fake news and achieved a good accuracy compared to existing natural language processing methods." @default.
- W4312907753 created "2023-01-05" @default.
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- W4312907753 date "2022-01-01" @default.
- W4312907753 modified "2023-09-27" @default.
- W4312907753 title "Fake news detection in social media using recurrent neural network" @default.
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- W4312907753 doi "https://doi.org/10.1063/5.0108649" @default.
- W4312907753 hasPublicationYear "2022" @default.
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