• Mr.N.Kesav Rao
• S.Jeenath Kumar

In the age of information overload, the proliferation of fake news has become a pressing issue with profound societal implications. Addressing this challenge requires innovative approaches that leverage the power of data science. This paper presents a comprehensive overview of the methodologies and techniques employed in the detection of fake news using data science.Firstly, the paper delves into the characteristics and typologies of fake news, emphasizing the importance of understanding its multifaceted nature. Subsequently, it provides an overview of the datasets commonly utilized in fake news detection research, highlighting the diversity of sources and formats that contribute to a robust analysis.The paper then explores various feature extraction techniques, including natural language processing (NLP) and sentiment analysis, which play a pivotal role in discerning patterns indicative of fake news.

Fake News Detection Using Data Science

"Fake News Detection Using Data Science", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.347-353, June-2024, Available :http://www.jetir.org/papers/JETIRGL06058.pdf

"Fake News Detection Using Data Science", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp347-353, June-2024, Available at : http://www.jetir.org/papers/JETIRGL06058.pdf