NLP-Driven Sentiment Analysis for Fake News Identification: The Responsive Truth
摘要
In the current era of technology news can often be considered more valuable than money. However, this information needs to be genuine, which is often not the case, leading to a pressing need to distinguish real news from fake news. News, as a form of information, is subjective and relies heavily on proof and source credibility. People can typically discern real news from falsehoods through their innate ability to apply logic and recognize dubious sources. However, having a few trusted sources for fact-checking is essential. There is an urgent demand for software solutions that can quickly address the spread of false news, making this a highly researched area. As part of Information Retrieval, it has garnered significant attention from researchers worldwide seeking real-time solutions. In this article, we analyze various research and survey articles to provide readers with a concise overview of fake news, its various forms, characteristics, and identification basics. We can reasonably conclude that the majority of fake news is spread with the purpose of instilling hatred and resentment in Indian society.