Hate Speech Detection in English and Non-English Languages: A Review of Techniques and Challenges
Year: 2021
Type: article
Abstract: The exponential growth of social media has spurred an increase in the propagation of hate nowadays. Recent evidence shows that hate speech on social media is detrimental to the mental and physical health of individuals. Thus, there is an emerging need for automated hate speech detection. Automated hate speech detection rests on the intersection between Natural Language Processing (NLP) techniques and machine learning models. An introduction of NLP and its utilities, as well as commonly employed features and classification methods in hate speech detection, are discussed. Hate speech detection in non-English languages is needed to tackle this emergent issue in countries where multiple languages are used. Hence, an overview of the current literature on hate speech detection in non-English languages are covered too. Challenges in the field of hate speech detection are explored and the importance of standardized methodologies for building corpora and data sets are emphasized.
Source: Webology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3209706435