| Summary: | English profanities (i.e. potentially offensive words, including swear words) have been in use for decades in the Nordic languages – Icelandic, Norwegian, Danish, Swedish and Finnish – and offer a multitude of opportunities for linguistic expression, along with the domestic, heritage profanities in each language. The Nordic countries present an interesting context for studying the impact of English on languages in remote-contact settings, where many, especially young people, are bilingual but English has no official status. While previous studies have mostly focused on the function of such words and investigated their appearance in each Nordic language in isolation, this study utilizes social media data from the Nordic Tweet Stream (Laitinen et al., 2018) to compare the forms and frequencies of the English profanities fuck, shit, ass, damn, bitch and hell across the Nordic languages, shedding light on the factors which are conducive to their use. Surprisingly, the English profanities were many times more frequent in the Icelandic material compared to the other languages, although Iceland has a strong tradition of linguistic purism and frequencies were expected to be lower than in the other languages. Contrastingly, the profanities were found to be morphologically and orthographically adapted to a higher degree in Icelandic, reflecting the purist tradition in other ways. Frequencies in the other four languages did not quite match the findings of previous studies on loanwords in the Nordic languages, while degrees of adaptation were more similar to previous results. Comparing the frequencies of the English profanities in this study with the frequencies of heritage profanities on Twitter found by Coats (2021) showed that, although especially fuck and shit are on par with and sometimes more frequent than the most frequent heritage profanities, they do not seem to be replacing domestic equivalents. Finally, through exploiting the geo-location tags that accompany each tweet in the Nordic Tweet Stream, the frequencies ...
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