Characterising Online News Comments: A Multi-Dimensional Cruise Through Online Registers

News organisations often allow public comments at the bottom of their news stories. These comments constitute a fruitful source of data to investigate linguistic variation online; their characteristics, however, are rather understudied. This paper thus contributes to the description of online news comments and online language in English. In this spirit, we apply multi-dimensional analysis to a large dataset of online news comments and compare them to a corpus of online registers, thus placing online comments in the space of register variation online. We find that online news comments are involved-evaluative and informational at the same time, but mostly argumentative in nature, with such argumentation taking an informal shape. Our analyses lead us to conclude that online registers are a different mode of communication, neither spoken nor written, with individual variation across different types of online registers.

Registerial Adaptation vs. Innovation Across Situational Contexts: 18th Century Women in Transition

Endeavors to computationally model language variation and change are ever increasing. While analyses of recent diachronic trends are frequently conducted, long-term trends accounting for sociolinguistic variation are less well-studied. Our work sheds light on the temporal dynamics of language use of British 18th century women as a group in transition across two situational contexts. Our findings reveal that in formal contexts women adapt to register conventions, while in informal contexts they act as innovators of change in language use influencing others. While adopted from other disciplines, our methods inform (historical) sociolinguistic work in novel ways. These methods include diachronic periodization by Kullback-Leibler divergence to determine periods of change and relevant features of variation, and event cascades as influencer models.

Linguistic Variation and Change in 250 Years of English Scientific Writing: A Data-Driven Approach

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.