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Copyright

Marcus Scheiber

Published On

2024-06-21

Page Range

pp. 159–184

Language

  • English

Print Length

184 pages

6. Multimodal Cognitive Anchoring in Antisemitic Memes

Chapter of: Antisemitism in Online Communication: Transdisciplinary Approaches to Hate Speech in the Twenty-First Century(pp. 159–184)
The ongoing mediatisation and digitalisation of our lives has also resulted in an increasing dissemination of antisemitic concepts. Antisemitic evaluations that have existed for centuries are finding their way into online debates in new semiotic patterns and in innovative communication formats. Memes are one kind of these new communication formats, which prototypically have a text image structure and can be utilised to realise antisemitic concepts that are anchored in cultural memory. This chapter explores the production and reception processes of these anchored concepts in antisemitic memes by showing the patterns of cognitive processing that allow the integration of verbal and pictorial sign potentials within the meme format via the processes of blending.

Contributors

Marcus Scheiber

(author)
PhD Candidate at University of Vechta
PhD Student at University of Vienna
https://orcid.org/0009-0006-1714-2015

Marcus Scheiber is a linguist with research interests in social semiotics, corpus linguistics, Critical Discourse Analysis and multimodality research. He started his academic career at the Universities of Heidelberg and Bern and, as a visiting researcher and lecturer, at the University of Mumbai. He received his MA from the University of Heidelberg in 2018 with a thesis about internet memes. Since 2020, he has been pursuing a joint PhD project at the University of Vechta and University of Vienna entitled “The reality construction potential of multimodal communicative units in antisemitic communication”, examining internet memes as communication formats in antisemitic communication strategies. In addition to his academic pursuits, he was employed as a data analyst at Amazon, where he was responsible for the further development and improvement of Alexa through qualitative annotation and transcription of speech data.