Hate Text Finder Using Logistic Regression

EasyChair Preprint 8312

Abstract

Hate Text means a message designed to degrade, intimidate or incite violence or prejudicial action against a person or group of people based on their race, gender, ethnicity, nationality, religion, political affiliation, language, ability or appearance . So, Governments and social media providers put an effort to tackle offensive, abusive, and profanity in social media as an abuse of speech freedom. Considering the number of Internet users in the world and theconflict caused by offensive content involved in posts, there is an urge to develop offensive content detection for posts. This project uses a logistic regression model for classifying the words as (non)offensive words. This model can assist the government in enforcing the information and decreases the number of disputes due to aspiration freedom abuse on social media. In this project, we developed a social blog to demonstrate this entire process and it shows good results. We are testing whether the post contains offensive content or not at the time of posting itself.

Keyphrases: Blog Posting and Viewing, Offensive., User Authentication, hostile, logistic regression

@booklet{EasyChair:8312,
  author    = {Ravikanti Vaishnavi and Kumbam Venkatreddy and Vangapati Nagamani and Mettu Sai Madhava Reddy},
  title     = {Hate Text Finder Using Logistic Regression},
  howpublished = {EasyChair Preprint 8312},
  year      = {EasyChair, 2022}}