A State-of-the-Art of Semantic Change Computation
It provides a framework for researchers in computational linguistics, but it is incremental as it summarizes existing work without introducing new methods or results.
This paper reviews the state-of-the-art in semantic change computation, identifying five essential components in the field and highlighting that current studies primarily test hypotheses from theoretical linguistics, with core issues like limited language corpora and evaluation data remaining unsolved.
This paper reviews the state-of-the-art of semantic change computation, one emerging research field in computational linguistics, proposing a framework that summarizes the literature by identifying and expounding five essential components in the field: diachronic corpus, diachronic word sense characterization, change modelling, evaluation data and data visualization. Despite the potential of the field, the review shows that current studies are mainly focused on testifying hypotheses proposed in theoretical linguistics and that several core issues remain to be solved: the need for diachronic corpora of languages other than English, the need for comprehensive evaluation data for evaluation, the comparison and construction of approaches to diachronic word sense characterization and change modelling, and further exploration of data visualization techniques for hypothesis justification.