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: “general debate hate speech versus freedom of expression”,“hate-speech automatic detection and classification by machine-learning strategies”, and “gendered hate speech and cyberbullying”. The understanding of how research fronts interact led to stress the relevance of machine learning approaches to correctly assess hatred forms of online speech.
Highlights
In recent years, the ways in which people receive news, and communicate with one another, have been revolutionised by the Internet, and especially by social networks
In the same vein of Waqas et al (2019), we focus on online hate and, for our search, we built a query that, in addition to the exact phrase “hate speech”, combines terms related to offensive or denigratory language (“hatred”, “abusive language, “abusive discourse”, “abusive speech”, “offensive language”, “offensive discourse”, “offensive speech”, “denigratory language”, “denigratory discourse”, “denigratory speech”) with words linked to the online nature (“online”,“social media”, “web”, “virtual”, “cyber”, “Orkut”, “Twitter”, “Facebook”, “Reddit”, “Instagram”, “Snapchat”, “Youtube”, “Whatsapp”, “Wechat”, “QQ”, “Tumblr”, “Linkedin”, “Pinterest”)
We concentrated on the yearly quantitative distribution of literature, we examined the conceptual structure of hate speech research
Summary
The ways in which people receive news, and communicate with one another, have been revolutionised by the Internet, and especially by social networks. It is a natural activity, in societies where freedom of speech is recognised, for people to express their opinions. Countries are recognising hate speech as a serious problem, and this has led to a number of International and European initiatives being proposed, aimed at qualifying the problem and developing effective counter-measures
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