Almans and Kanaks: Inter-cultural Stereotypes in a German Twitter Corpus

This paper examines inter-cultural stereotypes in a large German Twitter Corpus (2 billion
words). The main focus is on hetero- and auto-stereotypes found within the Turkish and Arab
immigrant community in Germany, and since much of the relevant German-language data is
influenced by the Kietzdeutsch sociolect, the term Alman (Turkish for ‘German’) is used as a
window into the corpus. The term is contrasted with the German slur Kana(c)ke (‘foreigner’)
and both investigated for associated stereotypes in both qualitative and quantitative ways,
using concordances and relevant linguistic patterns (e.g. generalization and othering), as
well as relative frequencies, sentiment analysis and word vector distances based on emoji
classification. In connection with negative stereotyping, we discuss examples of “counter
hate speech” directed by (part of) the immigrant minority at the German majority. Finally,
we investigate the role of humour and jokes as vehicles of stereotypes.