mlsanityData to 7 Oct 2026

DRIFT: A Toolkit for Diachronic Analysis of Scientific Literature

arXiv 2107.01198 ↗First posted 2 Jul 2021cs.CLcited by 4

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Abstract (arXiv)

In this work, we present to the NLP community, and to the wider research community as a whole, an application for the diachronic analysis of research corpora. We open source an easy-to-use tool coined: DRIFT, which allows researchers to track research trends and development over the years. The analysis methods are collated from well-cited research works, with a few of our own methods added for good measure. Succinctly put, some of the analysis methods are: keyword extraction, word clouds, predicting declining/stagnant/growing trends using Productivity, tracking bi-grams using Acceleration plots, finding the Semantic Drift of words, tracking trends using similarity, etc. To demonstrate the utility and efficacy of our tool, we perform a case study on the cs.CL corpus of the arXiv repository and draw inferences from the analysis methods. The toolkit and the associated code are available here: https://github.com/rajaswa/DRIFT.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 12 of its 23 references that are in the map. First posted on arXiv 2 Jul 2021.

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12 of 23 references.

References · 12

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  11. 2019The State of NLP Literature: A Diachronic Analysis of the ACL Anthologycited by 8
  12. 2020NLP Scholar: An Interactive Visual Explorer for Natural Language Processing Literaturecited by 8

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Cited by year

Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 1.

4 papers.