This chapter raises three questions: a) concerns a synthesis of the classic contributions of the reference semiotic authors that are considered when analysing hate speech in social media; b) entails presenting a case study that is analysed precisely with that analysis synthesis; c) shows the usefulness and interest of this type of analysis in investigations of hate speech. It offers a semiotic model for analysing misogynistic and xenophobic hate speech from digital news media on Twitter. The case study comprises the news published by El Mundo (Spain) from its users on social media, and the 33 comments generated, as a reason for this publication, during January 2021. This serves as the basis of semiotic analysis for understanding the phenomenon. The results visualise the semiotic analyses for understanding the dissemination of expressions. This approach thus helps reveal the levels of intensity, the denotative and connotative differences, the destructive-constructive and intertextual nature of messages, and sheds light on the different symbolic structures associated with hate speech.
TopBackground
The research analysing hate speech on digital media has grown. This interest reflects the propagation capacity of these scenarios, which favour a predominantly anonymous character and high emotional charge. All of this causes wide dissemination of misinformation content among many users of a specific social media platform. In these scenarios, openly xenophobic or misogynistic discourses proliferate from the multiplicity of interactions and the interactions generated by the abundance of information available in these digital communication contexts (Piñeiro-Otero & Martínez-Rolán, 2021).
Concerning xenophobic expressions from digital media, the number of studies on this topic is still low (Müller & Schwarz, 2020).
A review of these publications on xenophobia, using the Web of Science or Scopus, in current digital media presents just under fifty papers as of 2022 in journals in the communication area. Most have focused on designing detection models for this type of hate through algorithms (Amores et al., 2021; Benitez-Andrades et al., 2022; Plaza-Del-Arco et al., 2022; Silva et al., 2020). Another group has provided descriptions of their operations on social media (Twitter) and their relationships with social media, focusing on some instances such as vulnerable groups associated with immigration and refugees) and specific situations (during the COVID-19 pandemic or Brexit) (Breazu & Machin, 2022; Giraldo Pérez, 2022; Park, 2017; Sánchez-Holgado, et al., 2022; Zamri et al., 2021). To these are added the reviews and applications of policies and legal frameworks in different geographical contexts (e.g., Europe and the United States), how political movements (e.g., nationalists and extreme right) favour the dissemination of these expressions through the internet, social media and official channels of the state, and ethnography, critical discourse rhetoric and cultural semiotics analysis (Alkiviadou, 2018; Arrocha, 2019; Bourou, 2022; Brindle, 2016; Damcevic & Rodik, 2018; Evenden-Kenyon, 2019; Guizardi & Mardones, 2020; Khoma & Oleksii Kokoriev, 2021; Tymińska, 2020; Sumalla, 2018; Yamaguchi, 2013). Finally, the complementary professional activity required by this type of hate speech has been analysed regarding digital newspapers (Merklejn & Wislicki, 2020; Paz-Rebollo et al., 2021; Slavíčková & Zvagulis, 2014).
Misogynistic expressions involve contempt towards, the humiliation of or the disclosure of prejudice against a woman or a group of women (European Commission against Racism and Intolerance, 2016); similar to xenophobic expressions, they have found an environment favourable to their expression of social media (Ging, 2019). Their effects on society transcend the individual sphere, as they favour the promotion of stereotypes against the collective (Megías et al., 2020).