Tracing Research Paradigm Change Using Terminological Methods. A Case Study on "Machine Translation" in the ACL Anthology Reference Corpus

This paper explores the use of terminology extraction methods for detecting paradigmatic changes in scientific articles. We use a statistical method for identifying salient nouns and adjectives that signal these paradigmatic changes. We then employ the extracted lexical units for discovering terms that are assumed to be central in characterising paradigm shifts. To assess the method’s performance, in this pilot study, we work on “machine translation” (MT) research articles sampled from the ACL anthology reference corpus. We analyse this corpus to check whether the proposed approach can trace the dramatic changes that machine translation research has experienced in the last decades: from transformational rule-based methods to statistical machine learning-based techniques.