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VOL. 10, ISSUE 2 (2025)
AI-powered fake news detection: Leveraging machine learning and NLP for automated fact-checking
Authors
Ukanwolu Grace Ngozi, Omankwu Obinnaya Chinecherem Beloved
Abstract
Fake news has become a significant challenge in the digital age,
influencing public opinion, shaping political discourse, and affecting
decision-making processes. This study presents an AI-driven approach to fake
news detection using machine learning and deep learning techniques, with a
focus on sentiment analysis and natural language processing (NLP). The research
involves data collection, preprocessing, feature extraction, model training,
and evaluation to develop an effective and interpretable detection system. A
labeled dataset was sourced from Kaggle.com, containing both real and fake news
articles. Preprocessing techniques such as text normalization, tokenization,
stopword removal, stemming, and lemmatization were applied to clean and
standardize the text. Feature extraction methods, including TF-IDF, Word2Vec,
and BERT embeddings, were used to convert textual data into numerical
representations suitable for machine learning models. Various models, including
Logistic Regression, Support Vector Machines (SVM), Random Forest, LSTM, and
BERT, were trained and evaluated using metrics such as accuracy, precision,
recall, and F1-score. The implementation leveraged powerful tools such as
Python, Pandas, NLTK, Scikit-Learn, TensorFlow, and PyTorch for model
development and analysis. Experimental results demonstrated that incorporating
sentiment-based and textual features significantly improves classification
accuracy. The study provides a robust and scalable AI-based framework for
automated fact-checking and misinformation detection. The findings contribute
to combating the spread of fake news, with potential applications in content
moderation on social media platforms and real-time misinformation detection
systems.
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Pages:26-31
How to cite this article:
Ukanwolu Grace Ngozi, Omankwu Obinnaya Chinecherem Beloved "AI-powered fake news detection: Leveraging machine learning and NLP for automated fact-checking". International Journal of Academic Research and Development, Vol 10, Issue 2, 2025, Pages 26-31
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