Abstract
We trace the evolution of Scientific English through the Late Modern period to modern time on the basis of a comprehensive corpus composed of the Transactions and Proceedings of the Royal Society of London, the first and longest-running English scientific journal established in 1665. Specifically, we explore the linguistic imprints of specialization and diversification in the science domain which accumulate in the formation of “scientific language” and field-specific sublanguages/registers (chemistry, biology etc.). We pursue an exploratory, data-driven approach using state-of-the-art computational language models and combine them with selected information-theoretic measures (entropy, relative entropy) for comparing models along relevant dimensions of variation (time, register). Focusing on selected linguistic variables (lexis, grammar), we show how we deploy computational language models for capturing linguistic variation and change and discuss benefits and limitations.
Highlights
The language of science is a socio-culturally firmly established domain of discourse that emerged in the Early Modern period and fully developed in the Late Modern period
2001; Leech et al, 2009), the Late Modern period is a very prolific time when it comes to the formation of text types, with many of the registers we know today developing during that period—including the language of science
This behavior is not consistent with a raw frequency effect, or with the side effects of changes in the magnitude of training data. It looks like the distributional profile of words is, on average, growing more distinct in this specific corpus. This does not happen only for new vocabulary, created ad hoc for specific contexts: even when we factor out the changes in lexicon and we consider only those words that appear in every decade (Persistent Vocabulary in Table 3), the effect is still visible
Summary
The language of science is a socio-culturally firmly established domain of discourse that emerged in the Early Modern period (ca. 1500–1700) and fully developed in the Late Modern period (ca. 1700–1900). While there is a fair stock of knowledge on the development of scientific language from socio-cultural and historical-pragmatic perspectives (see section 2), it is less obvious what are the underlying, more general principles of linguistic adaptation to new needs of expression in an increasingly diversified and specialized setting such as science. This provides the motivation for the present research. We start with an overview of previous work in corpus and computational linguistics in modeling diachronic change with special regard to register and style (section 2). We summarize our main results and briefly assess benefits and shortcomings of the different kinds of models and measures applied to the analysis of linguistic variation and change (section 5)
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