Abstract
AbstractEnglish has firmly established itself as a lingua franca in the international environment and in no environment is this more true than in the academic one. Self-mention, especially in academic settings, has been studied extensively; however, not so in written ELF (English as a Lingua Franca) academic discourse, as the prevailing focus of ELF studies has been on the spoken form. In this corpus-based study, I choose Walková’s (2019) three-dimensional model of self-mention and apply it in the self-mention analysis in the SSH category of the SciELF corpus, a corpus of unpublished research articles written by ELF users. The results are compared with the reference corpus CSSH compiled to be comparable to the SSH corpus in terms of discipline. Features related to self-reference are chosen to represent each dimension. The results are tested for statistical significance using the Log-likelihood test. Some data proved to be of greater statistical significance (the use of personal pronouns) while other data did not carry any (the use of boosters).
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