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A Glimpse into Terminology Research with R: Two Experiments Exploring Diastratic Variation in a Large Specialized Corpus

Master program titleMaîtrise universitaire en traduction et technologies mention Terminologie
Defense date2021
Abstract

The increasing possibilities for the study of specialized discourse have seen terminologists dealing with larger and more heterogenous corpus data, a context in which ready-made tools might fall short. This work investigates if the R programming language can help researchers analyze complex specialized corpora and uncover clues of diastratic variation in language for specific purposes, a phenomenon understood as the coexistence of different language uses among groups of experts in the same field. Since one selling point of R is its capacity to stay up to date with techniques in both statistics and machine learning, an experiment is proposed in each of these areas: one dives into the exploratory analysis of categorical data, while the other relies on distributional semantics and deep-learning technology. Together, these series of tests make it possible to discuss key perspectives and limitations for R in terminology studies.

eng
Keywords
  • R
  • specialized corpora
  • large corpora
  • diastratic variation
  • exploratory statistics
  • distributional analysis
Citation (ISO format)
GONZALEZ GRANADO, Nicolas. A Glimpse into Terminology Research with R: Two Experiments Exploring Diastratic Variation in a Large Specialized Corpus. 2021.
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Master thesis
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Identifiers
  • PID : unige:153976
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Creation08/18/2021 1:47:00 PM
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