AI-BASED FAKE NEWS DETECTION

Fake news became one of the main problems in the information space due to the possibility of publishing texts online. Artificial Intelligence, Machine Learning, and Natural Language Processing offer effective techniques and tools for addressing this issue by analyzing large amounts of data and finding patterns specific to each news article. The paper described an AI-based approach to detecting fake news, including the data collection, preprocessing, feature extraction, training, classification, and evaluation stages. The findings demonstrated that conventional machine-learning techniques can still be appropriate baselines in the fight against fake news, although there are more advanced options, such as deep learning and transformer-based networks, which are capable of achieving better performance on more complex tasks. The results also showed that data, domain adaptation, language variations, shifting computational complexity,and interpretability were major challenges in the research.

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