@inproceedings{mohammad-2020-nlp-scholar,
title = "{NLP} Scholar: An Interactive Visual Explorer for Natural Language Processing Literature",
author = "Mohammad, Saif M.",
editor = "Celikyilmaz, Asli and
Wen, Tsung-Hsien",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-demos.27",
doi = "10.18653/v1/2020.acl-demos.27",
pages = "232--255",
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.",
}
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%0 Conference Proceedings
%T NLP Scholar: An Interactive Visual Explorer for Natural Language Processing Literature
%A Mohammad, Saif M.
%Y Celikyilmaz, Asli
%Y Wen, Tsung-Hsien
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F mohammad-2020-nlp-scholar
%X 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.
%R 10.18653/v1/2020.acl-demos.27
%U https://aclanthology.org/2020.acl-demos.27
%U https://doi.org/10.18653/v1/2020.acl-demos.27
%P 232-255
Markdown (Informal)
[NLP Scholar: An Interactive Visual Explorer for Natural Language Processing Literature](https://aclanthology.org/2020.acl-demos.27) (Mohammad, ACL 2020)
ACL