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DRIFT: A Toolkit for Diachronic Analysis of Scientific Literature

2021-07-02 17:33:25
Abheesht Sharma, Gunjan Chhablani, Harshit Pandey, Rajaswa Patil
arXiv_CL
       
Abstract

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: this https URL.

Abstract (translated)

URL

https://arxiv.org/abs/2107.01198

PDF

https://arxiv.org/pdf/2107.01198.pdf

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