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Diachronic word embeddings and semantic shifts: a survey
AbstractRecent years have witnessed a surge of publications aimed at tracing temporal changes in lexical semantics using distributional methods, particularly prediction-based word embedding models. However, this vein of research lacks …...
Diachronic Sense Modeling with Deep Contextualized Word Embeddings: An Ecological View
AbstractDiachronic word embeddings have been widely used in detecting temporal changes. However, existing methods face the meaning conflation deficiency by representing a word as a single vector at each time …...
Empirical Study of Diachronic Word Embeddings for Scarce Data
AbstractWord meaning change can be inferred from drifts of time-varying word embeddings. However, temporal data may be too sparse to build robust word embeddings and to discriminate significant drifts from …...
Neural Temporality Adaptation for Document Classification: Diachronic Word Embeddings and Domain Adaptation Models
AbstractLanguage usage can change across periods of time, but document classifiers models are usually trained and tested on corpora spanning multiple years without considering temporal variations. This paper describes two …...
Text-based inference of moral sentiment change
AbstractWe present a text-based framework for investigating moral sentiment change of the public via longitudinal corpora. Our framework is based on the premise that language use can inform people’s moral …...