Using AI Models to Detect and Combat Fake News
Abstract: The spread of fake news and misinformation has become a global challenge, undermining public trust, causing political polarization, and facilitating the dissemination of harmful ideologies. This study explores the use of advanced AI models, specifically transformers such as BERT and GPT, for the automatic detection of fake news. Leveraging natural language processing (NLP) techniques like Named Entity Recognition (NER), Sentiment Analysis, and Topic Modeling, we aim to identify patterns unique to misinformation. Our model demonstrates high accuracy in experimental trials on benchmark datasets, highlighting the potential of AI to combat disinformation and improve media literacy.
Keywords: Fake news detection, AI in media, misinformation analysis, natural language processing
How to Cite?: Youssef Daoud, "Using AI Models to Detect and Combat Fake News", Volume 14 Issue 1, January 2025, International Journal of Science and Research (IJSR), Pages: 776-777, https://www.ijsr.net/getabstract.php?paperid=SR25113113848, DOI: https://dx.doi.org/10.21275/SR25113113848