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Enhancing the Predictive Performance of Credibility-Based Fake News Detection Using Ensemble Learning.
Amit Neil Ramkissoon1, Wayne Goodridge1
1Department of Computing & Information Technology, The University of the West Indies at St Augustine, St Augustine, Trinidad and Tobago.
This study introduces Legitimacy, an ensemble machine learning model for credibility-based fake news detection. Legitimacy achieves 96.9% accuracy, outperforming its base models and demonstrating scalability for improved fake news identification.
Area of Science:
- Computer Science
- Artificial Intelligence
- Machine Learning
Background:
- Fake news detection is a significant societal challenge, difficult even for advanced machine learning algorithms.
- Existing methods for classifying fake news are varied, but effective prediction remains elusive.
- Credibility-based features of news publishers are crucial for identifying misinformation.
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