Biography
Matthias is a linguist, with a strong focus on pragmatics, cognitive linguistics, (critical) discourse and media studies, research on prejudice and nationalism, as well as on internet/social media studies.
At Freie Universität Berlin, he read linguistics, philosophy and literature, and has worked in several research projects on the use of language in political and media campaigns. His doctoral dissertation, published with Nomos in 2018, analyses the linguistic construction of national pride, antisemitic stereotypes and demonising historical analogies in British and German discourses on the Israeli-Palestinian conflict. An English version of the book (with the title "Antisemitism in Reader Comments: Analogies for Reckoning with the Past") was published with Palgrave Macmillan in 2021.
Since 2019, Matthias is a postdoc researcher at the Centre for Research on Antisemitism (ZfA) at Technische Universität in Berlin. Furthermore, he is affiliated to CENTRIC (Sheffield Hallam University) and to the Vidal Sassoon Center at Hebrew University, Jerusalem. In his postdoc project, he examines various forms of antisemitic and racist hate speech on British news websites in the context of Brexit. Next to antisemitism, he conducted studies on the concept of national racism and antiziganism.
A consistent link between all his research activities is the question of how implicit hate speech - apparently accepted within various milieus of the political mainstream - is constructed and what conditions its production is subject to.
Organisation
Since 2021, the pilot project "Decoding Antisemitism: An AI-driven Study on Hate Speech and Imagery Online" (DA) has analysed the content and linguistic structure of thousands of antisemitic comments posted on social media and newspaper comment threads. Initially concentrating on the UK, Germany and France, the project will extend to other language communities in the future. Using the results of an innovative mode of qualitative corpus analysis as a guide, the project is now developing AI language models capable of recognising explicit and implicit forms of antisemitism. The twin-track methodology of this project, combining social science and humanities research with cutting-edge data and computer science, holds considerable promise for other forms of hate speech beyond antisemitism. It is with this potential in mind that the project is holding a symposium on how technology and academic research can work together to recognise, track and combat hate speech and social radicalisation.