Publication Date
Fall 2023
Document Type
Capstone Project
Degree Name
Master of Science
Department
Computer Science
First Advisor
Yunchuan Liu, Ph.D.
Second Advisor
Xin (Jasmine) Chen, Ph.D.
Third Advisor
Xueqing Tang, Ph.D.
Abstract
This application classification of online toxic comments using machine learning algorithms project was implemented for the Graduate Capstone Seminar Project for the Master of Science Degree with a Major in Computer Science. In this project, different Machine learning algorithms are used to find toxic comments. In discussions, toxic comments are disrespectful and abusive which makes other people leave the discussion. So, many social networking sites difficult to promote discussions effectively. The main aim of the project is to examine the data of online harassment and classify it into different labels to find toxicity correctly. In this project, we are going to use six machine learning algorithms, apply them to our data and find which algorithm is best by analyzing evaluation metrics for toxic comments classification. We will aim to examine the toxicity with high accuracy to limit its adverse effects and help organizations take the necessary steps.
Recommended Citation
Bolu, Shiva Kumar, "Classification of Online Toxic Comments Using Machine Learning Algorithms" (2023). All Capstone Projects. 679.
https://opus.govst.edu/capstones/679