NLP Scholar: An Interactive Visual Explorer for Natural Language Processing Literature

Abstract

As part of the NLP Scholar project, we created a single unified dataset of NLP papers and their meta-information (including citation numbers), by extracting and aligning information from the ACL Anthology and Google Scholar. In this paper, we describe several interconnected interactive visualizations (dashboards) that present various aspects of the data. Clicking on an item within a visualization or entering query terms in the search boxes filters the data in all visualizations in the dashboard. This allows users to search for papers in the area of their interest, published within specific time periods, published by specified authors, etc. The interactive visualizations presented here, and the associated dataset of papers mapped to citations, have additional uses as well including understanding how the field is growing (both overall and across sub-areas), as well as quantifying the impact of different types of papers on subsequent publications.

NLP4NLP+5: The Deep (R)evolution in Speech and Language Processing

“…The global aim of this series of studies was to investigate the speech and natural language processing (SNLP), research area through the related scientific publications, using a set of NLP tools, in harmony with the growing interest for scientometrics in SNLP [refer to Banchs, 2012 ; Jurafsky, 2016 ; Atanassova et al, 2019 ; Goh and Lepage, 2019 ; Mohammad, 2020a , b , c ; Wang et al, 2020 ; Sharma et al, 2021 and many more] or in various domains such as economics (Muñoz-Céspedes et al, 2021 ), finance (Daudert and Ahmadi, 2019 ), or disinformation (Monogarova et al, 2021 ).…”