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- W3156340054 abstract "Exposing Fake news is required in today's digital era. In this paper, we discussed several ways to detect the misleading content which the general public can follow. We also provide a detailed discussion of existing tools and extension which are already available for fake news detection. We present several systems designed by researchers to fight against misinformation. Several Fact-checking websites are discussed here to help social media users verify the information present in Social-media. The public should access these tools to determine the fabricated content. This paper will help the general public to know the basic techniques for fake news identification. We ran LSTM and BI-LSTM Classifier on existing Kaggle dataset and achieved 91.51% accuracy using Bi-LSTM classifier." @default.
- W3156340054 created "2021-04-26" @default.
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- W3156340054 date "2021-02-17" @default.
- W3156340054 modified "2023-09-25" @default.
- W3156340054 title "Evaluation of Tools and Extension for Fake News Detection" @default.
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- W3156340054 doi "https://doi.org/10.1109/iciptm52218.2021.9388356" @default.
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