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
Filters
Institutions
- Federal Polytechnic, Nasarawa, Nasarawa State 66
- Federal Polytechnic, Nekede, Imo State 54
- Federal Polytechnic, offa, Kwara State 20
- Federal Polytechnic, Oko, Anambra State 8
- Federal School of Biomedical Engineering, (LUTH), Idi-Araba, Lagos State 1
- Federal School of Surveying, Oyo, Oyo State 7
- Federal University of Agriculture, Abeokuta, Ogun State 19
- Federal University of Petroleum Resources, Effurun, Delta State 80
- Federal University of Technology Akure, Ondo State 24
- Federal University of Technology, Minna, Niger State 47