Detecting Insults in Social Commentary

Author
Prashant Ravi
View Count
1566
License
Creative Commons CC BY 4.0
Abstract

This report gives an overview of the various machine learning algorithms implemented to detect certain comments that may appear insulting to another participant on a social networking platform. Feature selection was performed using n-grams, and the WEKA machine learning toolkit was used to build supervised learning clasifiers, that provided an accuracy of 82% on the test dataset. The dataset was obtained from the popular data science competition portal, Kaggle.

Detecting Insults in Social Commentary