Analyse des néologismes affixaux par le biais De Sketch Engin
ANALYSIS OF AFFIXAL NEOLOGISMS USING SKETCH ENGINE

Summary/Abstract: This paper focuses on the use of the state-of-the-art corpus tool, Sketch Engine (SkE), which was created in 2004 at Masaryk University in Brno, Czech Republic, as part of research into lexical semantics. We will discuss the strengths and weaknesses of this tool based on our own experiences as researchers in lexical neology, particularly in studying the lexicon from the period of the SARS-CoV-2 virus spread (2020–2022) with affixation as the focus of research interest. The daily newspaper Libération was the primary and sole source for constructing our research sample related to the health crisis, referred to as LIBÉ. Regarding the structure of the article, we will briefly introduce the Czechorigin software and then proceed by applying its functions to our research. As Sketch Engine favours quantitative analysis and the collection of statistical data, it can be assumed that the main challenges for users involve processing qualitative data, particularly at the semantic level of language. The scientific results obtained may be useful not only for lexicographers but also for corpus linguists and others working on various languages and lexicons. Thus, Sketch Engine, as a text analysis software, has been in use for just over 20 years. Its primary role is to facilitate the work of researchers, helping them save time in order to focus on analysing data and interpreting results. It is therefore widely used in lexicography and serves as a basis for working with large-scale text corpora. The software retrieves word sketches, groups them based on grammatical relationships, and creates thesauri from the corpus. Additionally, Sketch Engine employs an extended version of the formal language CQL (Corpus Query Language), allowing for complex queries (Chalupníková and Volková 4). Our overarching goal in this research is to highlight the qualities and shortcomings of Sketch Engine in researching the creative potential of the lexicon emerging during the SARS-CoV-2 virus spread (2020–2022). A practical outcome of this study is to assist researchers in deciding whether or not to use Sketch Engine based on the objectives and nature of their research. We assume that the main challenges for users will be processing qualitative data, particularly at the semantic level of language. It remains to be seen how to deal with the affixes in this research and how to identify and sort them using this tool.

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