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
- Landmark University, Omu-Aran, Kwara State 1
- Lead City University, Ibadan, Oyo State 2
- Lens Polytechnic, offa, Kwara State. 227
- Madonna University, Elele, Rivers State 22
- Madonna University, Okija, Anambra State 2
- Mcpherson University, Seriki Sotayo, Ogun State 1
- Michael and Cecilia Ibru University, Owhrode, Delta State 1
- Michael Okpara University of Agriculture, Umudike 45
- Michael Otedola Col of Primary Educ. Epe, Lagos (affl To University of Ibadan) 8
- Modibbo Adama University, Yola, Adamawa State 16