A Novel Approach to Fake News Detection Using Generative AI
Keywords:Fake news, Misinformation, Detection, Reliable information, Text analytics, Article summarization, User behaviour, Twitter analytics, Authentic sources, LlamaIndex, WhatsApp bot, Large Language Model (LLM)
Fake news has a significant impact on society, making the detection of such misinformation crucial. It undermines trust in reliable information sources, distorts public opinions, and can even influence political outcomes. Detecting fake news is important to ensure that users receive accurate and authentic information, maintain a trustworthy news ecosystem, and prevent the spread of misinformation. Directly classifying a fake news to be fake on some parameters is not possible. Here, the news article will be evaluated on the main three parameters, first is Text Analytics which includes identifying the exaggerated or propagandistic statements or the type of speech is been used in the article like acceptable, non acceptable, offensive, etc. and also through summarization, we get the context about the article, second is user behaviour through twitter analytics guides to understand the user reaction towards the article on the real time basis and at last, through indexing the authentic source in the index of Large Language Model build using LlamaIndex. This methodology integrated with the whatsapp bot showcased the better result to identify the fake news and ensure the user that the news is authentic or not.
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