@article{ref1,
title="Thirty years of research into hate speech: topics of interest and their evolution",
journal="Scientometrics",
year="2021",
author="Tontodimamma, Alice and Nissi, Eugenia and Sarra, Annalina and Fontanella, Lara",
volume="126",
number="1",
pages="157-179",
abstract="The exponential growth of social media has brought with it an increasing propagation of hate speech and hate based propaganda. Hate speech is commonly defined as any communication that disparages a person or a group on the basis of some characteristics such as race, colour, ethnicity, gender, sexual orientation, nationality, religion. Online hate diffusion has now developed into a serious problem and this has led to a number of international initiatives being proposed, aimed at qualifying the problem and developing effective counter-measures. The aim of this paper is to analyse the knowledge structure of hate speech literature and the evolution of related topics. We apply co-word analysis methods to identify different topics treated in the field. The analysed database was downloaded from Scopus, focusing on a number of publications during the last thirty years. Topic and network analyses of literature showed that the main research topics can be divided into three areas: &quot;general debate hate speech versus freedom of expression&quot;,&quot;hate-speech automatic detection and classification by machine-learning strategies&quot;, and &quot;gendered hate speech and cyberbullying&quot;. The understanding of how research fronts interact led to stress the relevance of machine learning approaches to correctly assess hatred forms of online speech.<p /> <p>Language: en</p>",
language="en",
issn="0138-9130",
doi="10.1007/s11192-020-03737-6",
url="http://dx.doi.org/10.1007/s11192-020-03737-6"
}