DUKweb, diachronic word representations from the UK Web Archive corpus

Tsakalidis, Adam; Basile, Pierpaolo; Bazzi, Marya; Cucuringu, Mihai; McGillivray, Barbara

doi:10.1038/s41597-021-01047-x

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…However, training these models is stochastic, which results in arbitrary coordinate spaces. Model alignment is an essential step in allowing word2vec models to be compared [38,39]. Before alignment, each model has its own unique coordinate space (Figures 1A), and each word is represented within that space (Figure 1B).…”

Section: Resultsmentioning

confidence: 99%

Changing word meanings in biomedical literature reveal pandemics and new technologies

Nicholson

Alquaddoomi

Rubinetti

et al. 2022

Preprint

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While we often think of words as having a fixed meaning that we use to describe a changing world, words are also dynamic and changing. Scientific research can also be remarkably fast-moving, with new concepts or approaches rapidly gaining mind share. We examined scientific writing, both preprint and pre-publication peer-reviewed text, to identify terms that have changed and examine their use. One particular challenge that we faced was that the shift from closed to open access publishing meant that the size of available corpora changed by over an order of magnitude in the last two decades. We developed an approach to evaluate semantic shift by accounting for both intra- and inter-year variability using multiple integrated models. Using this strategy and examining year-by-year changes revealed thousands of change points in both corpora. We found change points for tokens including 'cas9', 'pandemic', and 'sars' among many others. The consistent change-points between pre-publication peer-reviewed and preprinted text were largely related to the COVID-19 pandemic. We developed a web app for exploration (https://greenelab.github.io/word-lapse/) that enables users to investigate individual terms. To our knowledge, this analysis is the first to examine the semantic shift in biomedical preprints and pre-publication peer-reviewed text, and it lays the foundation for future work to examine how terms acquire new meaning and the extent to which that process is encouraged or discouraged by peer review.

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Section: Resultsmentioning

confidence: 99%

Changing word meanings in biomedical literature reveal pandemics and new technologies

Nicholson

Alquaddoomi

Rubinetti

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The data sources that have been used to train diachronic word embeddings in recent years are diverse. Tsakalidis et al (2021), for example, used a corpus of websites from the UK called DUKweb, Brandl and Lassner (2019) used two newspaper corpora in English and German, and many researchers use the Google Books corpus (Boukhaled et al, 2019;Vijayarani and Geetha, 2020;Yüksel et al, 2021).…”

Section: Related Workmentioning

confidence: 99%

Tracking Semantic Shifts in German Court Decisions with Diachronic Word Embeddings

Braun

2022

Proceedings of the Natural Legal Language Processing Workshop 2022

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Language and its usage change over time. While legal language is arguably more stable than everyday language, it is still subject to change. Sometimes it changes gradually and slowly, sometimes almost instantaneously, for example through legislative changes. This paper presents an application of diachronic word embeddings to track changes in the usage of language by German courts triggered by changing legislation, based on a corpus of more than 200,000 documents. The results show the swift and lasting effect that changes in legislation can have on the usage of language by courts and suggest that using time-restricted word embedding models could be beneficial for downstream NLP tasks.

show abstract

Changing word meanings in biomedical literature reveal pandemics and new technologies

et al. 2023

View full text Add to dashboard Cite

While we often think of words as having a fixed meaning that we use to describe a changing world, words are also dynamic and changing. Scientific research can also be remarkably fast-moving, with new concepts or approaches rapidly gaining mind share. We examined scientific writing, both preprint and pre-publication peer-reviewed text, to identify terms that have changed and examine their use. One particular challenge that we faced was that the shift from closed to open access publishing meant that the size of available corpora changed by over an order of magnitude in the last two decades. We developed an approach to evaluate semantic shift by accounting for both intra- and inter-year variability using multiple integrated models. This analysis revealed thousands of change points in both corpora, including for terms such as ‘cas9’, ‘pandemic’, and ‘sars’. We found that the consistent change-points between pre-publication peer-reviewed and preprinted text are largely related to the COVID-19 pandemic. We also created a web app for exploration that allows users to investigate individual terms (https://greenelab.github.io/word-lapse/). To our knowledge, our research is the first to examine semantic shift in biomedical preprints and pre-publication peer-reviewed text, and provides a foundation for future work to understand how terms acquire new meanings and how peer review affects this process.

show abstract

DUKweb, diachronic word representations from the UK Web Archive corpus

Cited by 3 publications

References 30 publications

Changing word meanings in biomedical literature reveal pandemics and new technologies

Changing word meanings in biomedical literature reveal pandemics and new technologies

Tracking Semantic Shifts in German Court Decisions with Diachronic Word Embeddings

Changing word meanings in biomedical literature reveal pandemics and new technologies

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