How is information content distributed in RA introductions across disciplines? An entropy-based approach

Keywords: RA introductions, move analysis, CARS model, entropy, information theory, disciplinary differences


Recent years have witnessed a growing interest in research article (RA thereafter) introductions. Most previous studies focused on the macro structures, rhetorical functions and linguistic realizations of RA introductions, but few intended to investigate the information content distribution from the perspective of information theory. The current study conducted an entropy-based study on the distributional patterns of information content in RA introductions and their variations across disciplines (humanities, natural sciences, and social sciences). Three indices, that is, one-, two-, and three-gram entropies, were used to analyze 120 RA introductions (40 introductions from each disciplinary area). The results reveal that, first, in RA introductions, the information content is unevenly distributed, with the information content of Move 1 being the highest, followed in sequence by Move 3 and Move 2; second, the three entropy indices may reflect different linguistic features of RA introductions; and, third, disciplinary variations of information content were found. In Move 1, the RA introductions of natural sciences are more informative than those of the other two disciplines, and in Move 3 the RA introductions of social sciences are more informative as well. This study has implications for genre-based instruction in the pedagogy of academic writing, as well as the broadening of the applications of quantitative corpus linguistic methods into less touched fields.


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How to Cite
Xiao, W., Liu, J., & Li, L. (2022). How is information content distributed in RA introductions across disciplines? An entropy-based approach. Research in Corpus Linguistics, 10(1), 63-83.