EMNLP 2021system demonstrations10 citations

DRIFT: A Toolkit for Diachronic Analysis of Scientific Literature

Abheesht Sharma, Gunjan Chhablani, Harshit Pandey, Rajaswa Patil

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: https://github.com/rajaswa/DRIFT.

BibTeX
@inproceedings{sharma-etal-2021-drift,
    title = "{DRIFT}: A Toolkit for Diachronic Analysis of Scientific Literature",
    author = "Sharma, Abheesht  and
      Chhablani, Gunjan  and
      Pandey, Harshit  and
      Patil, Rajaswa",
    editor = "Adel, Heike  and
      Shi, Shuming",
    booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = nov,
    year = "2021",
    address = "Online and Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.emnlp-demo.40/",
    doi = "10.18653/v1/2021.emnlp-demo.40",
    pages = "361--371"
}
DRIFT: A Toolkit for Diachronic Analysis of Scientific Literature · EMNLP 2021