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India | Information Technology | Volume 10 Issue 10, October 2021 | Pages: 955 - 961
Fake Text Identification using Feature Extraction
Abstract: Information preciseness on Internet, especially on social media, is a more and more vital concern, however, internet - scale facts hamper, ability to spot, evaluate, and proper such facts, referred to as "fake information, " found in those platforms. in the course of this paper, we propose an approach for "fake text" identification and ways to use it, one in each of the foremost famous online social media platforms, this undertaking is systematically characterizing the Web websites and reputations of the publishers of the false and actual information articles on their registration patterns, website online ages, area rankings, area popularity, and the possibilities of information disappearance from the Internet. The effects may also be advanced through making use of numerous strategies which might be discussed within side the paper.
Keywords: Latent Dirichlet Allocation, Natural Language Processing, Term Frequency - Inverse Document Frequency, Comma - Separated values, Structured Query Language
How to Cite?: Peketi Yamini, "Fake Text Identification using Feature Extraction", Volume 10 Issue 10, October 2021, International Journal of Science and Research (IJSR), Pages: 955-961, https://www.ijsr.net/getabstract.php?paperid=SR211011124307, DOI: https://dx.doi.org/10.21275/SR211011124307