A REVIEW ON A SMART SYSTEM FOR FAKE NEWS DETECTION

Author Reg. ID: TIJER_101502

Published Paper Id: TIJER2303171

Published In: Volume 10 Issue 3, March-2023

Abstract: In today's digital era, fake news is a growing worry since it is so simple to disseminate false information, which can have serious social and political repercussions. Detecting fake news is a critical task, but it can be challenging due to the rapidly changing nature of the news cycle and the various sources of misinformation. Machine learning techniques, such as natural language processing and deep learning, have shown promise in detecting fake news by analysing various features such as language patterns, source credibility, and social media engagement. These methods typically involve training models on large datasets of labelled news articles, using both textual and non-textual features. This abstract discusses the challenges of detecting fake news, the various machine learning techniques used, and the potential future directions for improving fake news detection. By developing more accurate and efficient methods for detecting fake news, we can help mitigate the negative effects of misinformation and promote more informed and accurate reporting.

Keywords: Fake news, Misinformation, Disinformation,Fact-checking,Machine Learning, Text Classification, Network analysis.

Downloads: 000236

Page No: 294-300

Country: Nagpur, Maharashtra, India

Research Area: Science and Technology

Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJER2303171

Published Paper PDF: https://tijer.org/TIJER/papers/TIJER2303171

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