Paper Contents
Abstract
With the rapid growth of social media, spreading fake news increasingly, fake news detection on social media platforms through the utilization of natural language processing (NLP) techniques. With the increasing prevalence of misinformation on social media, effective detection methods are crucial to mitigate the impact of false information. The survey examines various NLP-based approaches, including text classification, sentiment analysis, and linguistic feature extraction, employed for identifying fake news. Additionally, it investigates the challenges and limitations faced in this domain, such as the dynamic nature of language and the rapid spread of misinformation. The findings highlight the potential of NLP in detecting fake news on social media and the importance of ongoing research in refining and advancing these techniques for more accurate and timely identification.
Copyright
Copyright © 2024 Shahnawaz Alam. This is an open access article distributed under the Creative Commons Attribution License.
