Social Media Hate Speech Recognition through Text

Abstract

"Social media is an online network made up of people who share a common interest and want to communicate with one another. It is now widely acknowledged that social media has become the dominant issue in almost all parts of business and industry, as well as the leading mode of digital communication. With the rapid rise of social connections, communication between individuals of diverse sociocultural backgrounds has grown more explicit, leading to an increase in ""cyber"" confrontations. As a result, hate speech is increasingly being used, to the extent where it has now become a significant concern infiltrating these public forums(Mondal, Silva and Benevenuto, 2017). Hate speech is defined as the use of harsh, violent, or abusive language focusing on a particular group of people who share a similar characteristic, such as their gender (sexuality), ethnic group or race (discrimination), or religious beliefs and practices. As a result, it is necessary to detect such speech instantly and censor any content that contains hateful or inciting language.

The goal of this initiative is to address the issues associated with hate speech on social media. The proposed remedy was devised and implemented after identifying the existing gaps in the current system and determining the fundamental cause of the problem. This will help to reduce hate speech on social media and preserve a healthy, balanced, and positive experience for the user.

Many industry professionals and non-experts reviewed the executed approach to determining the system’s overall performance in tackling the specified concerns, and the feedback obtained validated the solution's utility and efficacy."