Development of Fake News Detection System Using Decision Tree Algorithm
Student: Abiodun Janet Arowolo (Project, 2025)
Department of Computer Science and Informatics
Lens Polytechnic, offa, Kwara State.
Abstract
ABSTRACT Fake 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: arowoloabiodun68@gmail.com
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Institutions
- Covenant University, Canaan Land, Ota, Ogun State 4
- Crawford University of Apostolic Faith Mission Faith City, Igbesa, Ogun State 2
- Crescent University, Abeokuta, Ogun State 1
- Cross Rivers University of Technology, Calabar, Cross Rivers State 144
- Delta State Polytechnic, Ogwashi-Uku, Delta State 14
- Delta State Polytechnic, Otefe, Delta State 13
- Delta State University, Abraka, Delta State 142
- Ebonyi State University, Abakaliki, Ebonyi State 18
- Edo University, Iyamho, Edo State 11
- Ekiti State University 61