The exponential growth of digital media has intensified the spread of misinformation, commonly known as fake news, posing serious social, political, and ethical challenges. This study examines the role of Artificial Intelligence (AI) in detecting and mitigating fake news across online platforms. Machine Learning (ML) and Natural Language Processing (NLP) techniques are analyzed to identify deceptive content based on linguistic patterns, sentiment polarity, and structural features of news articles. Using secondary data from publicly available datasets, statistical and AI-based models are evaluated for classification performance. Results indicate that fake news articles tend to exhibit more negative sentiment and slightly longer textual structures compared to real news, confirming the effectiveness of linguistic features as predictors.
Sajid et al. (Sat,) studied this question.