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
- UMA UKPAI SCHOOL OF THEOLOGY, UYO, AKWA IBOM STATE (AFFL TO UNIVERSITY OF UYO) 1
- Umaru Ali Shinkafi Polytechnic, Sokoto, Sokoto State 24
- Umaru Musa Yaradua University, Katsina, Katsina State 28
- Umca, Ilorin (Affiliated To University of Ibadan), Kwara State 1
- University of Abuja, Abuja, Fct 117
- University of Africa, Toru-Orua, Bayelsa State 4
- University of Benin, Benin City, Edo State 362
- University of Calabar Teaching Hospital School of Health Information Mgt. 1
- University of Calabar, Calabar, Cross River State 240
- University of Ibadan, Ibadan, Oyo State 14