Research trends in the control of hate speech on social media for the 2016-2022 time frame
The growth in the number of social media users has resulted in a corresponding rise in the spread of hate speech on these platforms, leading to a growing, but little studied, problem. The bibliometric study aimed to examine the research trend and identify the most productive authors, the most active...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universidad Pablo de Olavide (UPO) |
| Repositorio: | RIO. Repositorio Institucional Olavide |
| Idioma: | inglés |
| OAI Identifier: | oai:rio.upo.es:10433/22377 |
| Acceso en línea: | https://hdl.handle.net/10433/22377 |
| Access Level: | acceso abierto |
| Palabra clave: | Hate speech Social media Detection Machine learning Deep learning Natural language processing systems Bibliometric analysis |
| Sumario: | The growth in the number of social media users has resulted in a corresponding rise in the spread of hate speech on these platforms, leading to a growing, but little studied, problem. The bibliometric study aimed to examine the research trend and identify the most productive authors, the most active institutions, the leading countries and the most employed virtual hate speech control mechanisms by analyzing 576 relevant publications from the Scopus database published between 2016-2022. The findings showed an increase in publication and India as a leading country/region in research on virtual hate speech control mechanisms. Deep learning and natural language processing systems were identified as the most commonly used control mechanisms. Based on the results, it is recommended that future researchers focus on multidisciplinary collaboration and valid mechanisms for different languages. This paper provides a general overview of the current state of research in this field and serves as a guide for authors and institutions in their research and collaboration strategies. |
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