Katariya, Piyush, Gupta, Vedika, Arora, Rohan, Kumar, Adarsh, Dhingra, Shreya, Xin, Qin and Hemanth, Jude (2022) A deep neural network-based approach for fake news detection in regional language. International Journal of Web Information Systems, 18 (5-6). pp. 286-309. ISSN 1744-0084
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Abstract
The current natural language processing algorithms are still lacking in judgment criteria, and these approaches often require deep knowledge of political or social contexts. Seeing the damage done by the spreading of fake news in various sectors have attracted the attention of several low-level regional communities. However, such methods are widely developed for English language and low-resource languages remain unfocused. This study aims to provide analysis of Hindi fake news and develop a referral system with advanced techniques to identify fake news in Hindi
Item Type: | Article |
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Keywords: | Natural language processing | Fake news | Machine learning | Gated recurrent unit | Bidirectional LSTM (bi-LSTM) | Hyperparameters | Fine tuning |
Subjects: | Social Sciences and humanities > Social Sciences > Social Sciences (General) |
JGU School/Centre: | Jindal Global Business School |
Depositing User: | Amees Mohammad |
Date Deposited: | 29 Jul 2022 10:42 |
Last Modified: | 22 Feb 2023 11:29 |
Official URL: | https://doi.org/10.1108/IJWIS-02-2022-0036 |
URI: | https://pure.jgu.edu.in/id/eprint/3928 |
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