Geographic Citation Gaps in NLP Research

Mukund Rungta, Janvijay Singh, Saif M. Mohammad, Diyi Yang


Abstract
In a fair world, people have equitable opportunities to education, to conduct scientific research, to publish, and to get credit for their work, regardless of where they live. However, it is common knowledge among researchers that a vast number of papers accepted at top NLP venues come from a handful of western countries and (lately) China; whereas, very few papers from Africa and South America get published. Similar disparities are also believed to exist for paper citation counts. In the spirit of “what we do not measure, we cannot improve”, this work asks a series of questions on the relationship between geographical location and publication success (acceptance in top NLP venues and citation impact). We first created a dataset of 70,000 papers from the ACL Anthology, extracted their meta-information, andgenerated their citation network. We then show that not only are there substantial geographical disparities in paper acceptance and citation but also that these disparities persist even when controlling for a number of variables such as venue of publication and sub-field of NLP. Further, despite some steps taken by the NLP community to improve geographical diversity, we show that the disparity in publication metrics across locations is still on an increasing trend since the early 2000s. We release our code and dataset here: https://github.com/iamjanvijay/acl-cite-net
Anthology ID:
2022.emnlp-main.89
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1371–1383
Language:
URL:
https://aclanthology.org/2022.emnlp-main.89
DOI:
Bibkey:
Cite (ACL):
Mukund Rungta, Janvijay Singh, Saif M. Mohammad, and Diyi Yang. 2022. Geographic Citation Gaps in NLP Research. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 1371–1383, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
Geographic Citation Gaps in NLP Research (Rungta et al., EMNLP 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp-22-ingestion/2022.emnlp-main.89.pdf