University of Bahrain
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Combating Fake News: The Role of Effective Pre-Processing Techniques

Show simple item record Dhiman, Pummy Kaur, Amandeep Hamid, Yasir Anajemba, Joseph 2023-07-16T05:26:43Z 2023-07-16T05:26:43Z 2023-07-16
dc.identifier.issn 2210-142X
dc.description.abstract This study highlights the importance of detecting fake news and the necessity of effective pre-processing techniques to clean and merge datasets. By utilizing NLP techniques and Python programming, this study successfully merged two Indian datasets and performed pre-processing tasks to improve the quality of the data. The experiment section provides detailed insights into the process of merging and pre-processing, including code snippets and graphs to replicate the results. While this study contributes to the development of effective pre-processing techniques for fake news detection, there is still much work to be done in improving the accuracy of fake news detection. Future research can explore the use of deep learning classifiers and multimodality in fake news detection to enhance our ability to detect fake news and promote a more informed society. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject Fake News en_US
dc.subject India en_US
dc.subject Internet Access en_US
dc.subject Dataset en_US
dc.subject Natural Language Processing en_US
dc.title Combating Fake News: The Role of Effective Pre-Processing Techniques en_US
dc.volume 14 en_US
dc.issue 1 en_US
dc.pagestart 1 en_US
dc.pageend xx en_US
dc.contributor.authorcountry India en_US
dc.contributor.authoraffiliation Chitkara University en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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