We have found that potentially harmful names such as Chinese virus have been used intentionally and are accompanied by even more blatant cases of defamatory and accusatory language targeting the Chinese. Specifically, we intend to select the usages that are unequivocally intentional and whose aim is not only to emphasise the geographical origin of the virus, but also to justify blaming China for the global pandemic that SARS-CoV-2 eventually has caused. We use CDA as a framework for conducting a semantic analysis of expressions such as Asian virus, Chinese virus, Sinovirus or Wuhan virus used on Twitter. The present paper is maintained within the Critical Discourse Analysis (CDA) framework (van Dijk 1993), as CDA aims specifically to examine the ways in which discourses shape power relations, maintain social stigmas, perpetuate stereotypes and widen inequalities. The intention of the use of terms such as Chinese virus may be purely referential, but they are, nonetheless, marked with accusatory or downright racist overtones. Such names explicitly point to the geographical place of origin of the virus, but at the same time are likely to provoke associations and solidify pre-existing stereotypes about Asians as well as strengthen misconceptions about the virus itself. These ways of reference – although discouraged by the scientific community – still remain in frequent use in various COVID-19-related discourses. There are, however, other names which expose the Asian origin of the virus. The results show that online language producers adapt their texts to overcome limit constraints.Ģ019 saw the emergence of a new human pathogen, SARS-CoV-2, which causes a disease currently known as COVID-19. Consequently, they represent more informal language usage (e.g., internet slang) in turn, post-CLC tweets contained relatively more articles, conjunctions, and prepositions. (II) Token analysis: the relative frequency of tokens and bigrams (III) part-of-speech analysis: the grammatical structure of the sentences in tweets (i.e., adjectives, adverbs, articles, conjunctives, interjections, nouns, prepositions, pronouns, and verbs) pre-CLC tweets showed relatively more textisms, which are used to abbreviate and conserve character space. Three separate analyses were performed: (I) general analysis: the number of characters, words, and sentences per tweet, as well as the average word and sentence length. Pre-CLC tweets were compared with post-CLC tweets. We asked whether the character limit change (CLC) affected language usage in Dutch tweets and hypothesized that there would be a reduction in the need for character-conserving writing styles. This provided an opportunity for researchers to investigate the linguistic effects of length constraints in online communication. In November 2017 Twitter doubled the available character space from 140 to 280 characters.