Fake News Detection Using Decision Tree Algorithm
Student: Deborah Opeyemi Ayeni (Project, 2025)
Department of Computer Science
Lens Polytechnic, offa, Kwara State.
Abstract
ABSTRACTFake news nowadays is an important aspect in the life of social media, and in the political world. Fake news detection is an important research to be done for its detection but it has some challenges too. Some challenges can be due to less number of resources like an available dataset and published literature. I propose in this paper, a fake news detection using machine learning techniques. I compare different machine learning classification techniques. Not only that, but we will be working with one models that are, Decision Tree Classifier. According to my project’s finding I have achieved various accuracy of each method respectively. Our project can highly benefit to detect whether the given news is true or fake.
Keywords
For the full publication, please contact the author directly at: debbieadeayo@gmail.com
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Institutions
- AVE-MARIA UNIVERSITY, PIYANKO, NASARAWA STATE 1
- Babcock University, Ilishan-Remo, Ogun State 7
- Bamidele Olumilua University of Edu. Science and Tech. Ikere Ekiti, Ekiti State 454
- Bauchi State College of Agriculture, Bauchi, Bauchi State 1
- Bauchi State University, Gadau, Bauchi State 16
- Bayelsa State Polytechnic, Aleibiri, Bayelsa State 13
- Bayero University, Kano, Kano State 586
- Benue State Polytechnic, Ugbokolo, Benue State 10
- Benue State University, Makurdi, Benue State 47
- Bingham University, Karu, Nasarawa State 3