Genetic Programming Approach to Detect Hate Speech in Social Media

Genetic Programming Approach to Detect Hate Speech in Social Media
Author(s):
Nithin Kumar P, Narasimha M, P Neeraj Aravindhakshan, Sai Sanjan Reddy, Dr. Anitha K
Keywords:
Voting classifier, English Twitter dataset, Universal Sentence Encoder, GP.
Abstract
Now-a-days, social media has become part of our day to day lives. More than half of the world makes use of social media. With the increased use of social media, there have been many problems that are rising. Hate speech is one among them. Since there are billions of users using social media, it has become a big problem to deal with as it can be identified based on user’s report to such action. It’s difficult to monitor and detect the hate speech and on social media platforms. There is a need for detecting and avoiding the hate speech from circulating in social media. The language used and the size of the content pose problem for the traditional machine learning algorithms. Therefore, the genetic programming approach along with ml algorithm is used to detect hate speech because of the better performance it offers.
Article Details
Unique Paper ID: 155732 Publication Volume & Issue: Volume 9, Issue 1 Page(s): 1547 - 1552
Article Preview & Download

Share This Article

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org