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A Systematic Bibliometric Analysis of Hate Speech Detection on Social Media Sites

1, 1, 2, 1★★ Corresponding author

  1. 1Symbiosis Institute of Technology, Symbiosis International University (Deemed University), Pune, Maharashtra, INDIA.
  2. 2Hope Foundation’s International Institute of Information Technology, Pune, Maharashtra, INDIA.

CORRESPONDENCE

Ambika Pawar

Symbiosis Institute of Technology, Symbiosis International University (Deemed University), Pune, Maharashtra, INDIA.

ambikap@sitpune.edu.in

Received: 07-09-2021; Revised: 07-06-2022; Accepted: 19-03-2022.

Volume 11, Issue 1 · pp. 100-111 · 2022 · DOI: 10.5530/jscires.11.1.10

ABSTRACT

With the increasing availability of internet facilities for everyone across the globe, the internet plays an integral part in modern communication. People have the ease of contacting others and sharing thoughts and ideas quickly. This has raised an enormous amount of spread of Hate Speech on Online Social Media Sites. This paper aims to provide systematic bibliometric analysis and mappings of existing literature for Hate Speech Detection and to identify the existence of Hate speech-related research. Bibliometric Analysis of Machine Learning and Deep Learning articles in Hate, hostile, and abusive speech is considered. This is accomplished using the SCOPUS database, with tools like VOSViewer, Biblioshiny, and ScienceScape. Explored parameters consist of the document type, most active countries, top journals, relevant affiliations, trending topics, etc. It is observed that the current literature on hate speech is concentrated on a specific philosophy. An unexpected need to rectify this situation was evident from this bibliometric analysis due to recent occurrences of hate speech in the digital world.

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    Gangurde, A., Mankar, P., Chaudhari, D., & Pawar, A. (2022). A Systematic Bibliometric Analysis of Hate Speech Detection on Social Media Sites. Journal of Scientometric Research, 11(1), 100-111. https://doi.org/10.5530/jscires.11.1.10

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    © 2022 Author(s)

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. CC BY-NC-SA 4.0