Scientific writing is assumed to have become more informationally dense over time (Halliday, 1988; Biber and Gray, 2016). Given that scientific writing is intended for communication between experts, we hypothesize a tendency towards optimizing language use by striving for a balance between highly informative content and a conventionalized style of writing. We study this by means of fractal analysis, asking whether the degree of informativity has become more persistent with predictable patterns of gradual changes between high vs. low informational content, indicating a trend towards an optimal code for scientific communication. Specifically, surprisal is used to measure informativity and the Hurst exponent is used as a long-term dependence measure for fractality analysis, quantifying the degree of persistence of informativity in scientific texts.
CITATION STYLE
Bizzoni, Y., & Degaetano-Ortlieb, S. (2023). Fractality of informativity in 300 years of English scientific writing. In EACL 2023 - 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Proceedings of LaTeCH-CLfL 2023 (pp. 38–44). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.latechclfl-1.5
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