Detection of Hate Speech on Social Media Using Machine Learning

Mahima Shrimal; Harsh Kukreja; Pankaj Singh; Harsh Sharma; Piyush Rawat

International Journal of Software Computing and Testing

Detection of Hate Speech on Social Media Using Machine Learning

Abstract

As we know, social media platforms are the fastest method of communication because information is transmitted and received virtually instantaneously. Social media platforms' development radically altered how people communicate in our world, and one effect of these changes is a rise in inappropriate behaviors, like the use of derogatory language online. It might be challenging to express harsh or disrespectful ideas to someone right in the face. People believe it is safe to abuse or post inappropriate content online. Hate speech can be detrimental to an individual or a community. The prevalence of hate speech on social media is widely acknowledged to be a serious issue. Techniques for detecting hate speech have received major investment from numerous governments and organizations, and they have also caught the interest of the scientific community. Since each proposed method has its own benefits and drawbacks, it is still challenging to evaluate how well it performs despite the abundance of literature on the subject. Filtering or blocking such content on the Web depends on its detection. Massive amounts of text data require manual processing and classification, which takes time and effort. To recognize this kind of content, however, automatic approaches are crucial because of the enormous quantity of data that is posted day by day. we used machine learning techniques like natural language processing, logistic regression, and random forest.

Full text

The full text of this article is available to subscribers.

On a subscribing campus you are let in by network address, with no login at all.

One-off purchase. Permanent access to this article, no account needed.

A year of online access to every article in International Journal of Software Computing and Testing. Or choose several journals →

How to cite

Mahima Shrimal, Harsh Kukreja, Pankaj Singh, Harsh Sharma, Piyush Rawat. Detection of Hate Speech on Social Media Using Machine Learning. International Journal of Software Computing and Testing. 2023;8(2):1–6.

Download the citation:

Article details

Detection of Hate Speech on Social Media Using Machine Learning

Abstract

Read more of it

Publish your article

Abstract

Related articles

The Role of Artificial Intelligence in Mental Health: New Approaches for Diagnosis and Treatment

AI-Assisted Code Generation: Integrating Natural Language Models with Compiler Frameworks for Enhanced Software Development

A Machine Learning Framework for Fake News Detection Using Embeddings and Dimensionality Reduction

A Secured Check-In and Check-Out System Using Private Key Authentication and QR Code Verification Techniques for Daycare Management

Hybrid Evolutionary Algorithm for Automated Test Case Generation in Large-Scale Software Systems

Read more of it

Publish your article