Shlomo Argamon is Professor of Computer Science and Director of the Master of Data Science Program at the Illinois
Institute of Technology (USA). In this article, he reflects on the current and potential relationship between register and the
field of computational linguistics. He applies his expertise in computational linguistics and machine learning to a variety of
problems in natural language processing. These include stylistic variation, forensic linguistics, authorship attribution, and
biomedical informatics. He is particularly interested in the linguistic structures used by speakers and writers, including
linguistic choices that are influenced by social variables such as age, gender, and register, as well as linguistic choices that
are unique or distinctive to the style of individual authors. Argamon has been a pioneer in computational linguistics and NLP
research in his efforts to account for and explore register variation. His computational linguistic research on register draws
inspiration from Systemic Functional Linguistics, Biber’s multi-dimensional approach to register variation, as well as his own
extensive experience accounting for variation within and across text types and authors. Argamon has applied computational methods
to text classification and description across registers – including blogs, academic disciplines, and news writing – as well as the
interaction between register and other social variables, such as age and gender. His cutting-edge research in these areas is
certain to have a lasting impact on the future of computational linguistics and NLP.
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