FAKE NEWS DETECTION USING LSTM DEEP LEARNING
S. S. Sneha Priscilla A. Dhivya · Zenodo (CERN European Organization for Nuclear Research) · 2023
Newspapers are the primary source of news for people worldwide. However, offlate, due to the significant growth and updates in technologies, there has been astupendous rise in the popularity of social media. As a consequence, social networks such as social media, websites, blogs, etc. have emerged as relevant platforms togather all kinds of news. People rely more on social networks than newspapers thesedays. This survey paperdescribes the various methods and models used for the detection of fake news. Our project aims to use Natural Language Processing to directly detect fake news, basedon the text content of news articles. The model building and testing are done using Jupyter Notebook 6.4.11 and the news article is classified by using website which isdone in HTML5, CSS3 and Flask 2.1.2. Our aim is to find a reliable and accurate model that classifies given news article as either fake or true using machine learningor deep learning techniques.