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NLP Scholar: a dataset for examining the state of NLP research

From National Research Council Canada

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Affiliation
  1. National Research Council of Canada. Digital Technologies
FormatText, Article
Conference12th Conference on Language Resources and Evaluation [Held Virtually], May 11-16, 2020, Marseille, France
Subjectscientometrics; trends in research; Google Scholar; ACL Anthology; citations
Abstract
Google Scholar is the largest web search engine for academic literature that also provides access to rich metadata associated with the papers. The ACL Anthology (AA) is the largest repository of articles on Natural Language Processing (NLP). We extracted information from AA for about 44 thousand NLP papers and identified authors who published at least three papers in AA. We then extracted citation information from Google Scholar for all their papers (not just their AA papers). This resulted in a dataset of 1.1 million papers and associated Google Scholar information. We aligned the information in the AA and Google Scholar datasets to create the NLP Scholar Dataset—a single unified source of information (from both AA and Google Scholar) for tens of thousands of NLP papers. NLP Scholar can be used to identify broad trends in productivity, focus, and impact of NLP research. We present here initial work on analyzing the volume of research in NLP over the years and identifying the most cited papers in NLP. We also list a number of additional potential applications.
Publication date
PublisherEuropean Language Resource Association (ELRA)
In
  • Proceedings of the Conference on Language Resources and Evaluation (LREC 2020): 868–877.
LanguageEnglish
Peer reviewedYes
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Record identifierdf3a2ffa-2418-4adc-9fe3-e9adc2aac0f3
Record created2020-11-02
Record modified2020-11-06
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