Impact of COVID-19 in Natural Language Processing Publications: a Disaggregated Study in Gender, Contribution and Experience

Christine Basta, Marta R. Costa-jussa


Abstract
This study sheds light on the effects of COVID-19 in the particular field of Computational Linguistics and Natural Language Processing within Artificial Intelligence. We provide an inter-sectional study on gender, contribution, and experience that considers one school year (from August 2019 to August 2020) as a pandemic year. August is included twice for the purpose of an inter-annual comparison. While the trend in publications increased with the crisis, the results show that the ratio between female and male publications decreased. This only helps to reduce the importance of the female role in the scientific contributions of computational linguistics (it is now far below its peak of 0.24). The pandemic has a particularly negative effect on the production of female senior researchers in the first position of authors (maximum work), followed by the female junior researchers in the last position of authors (supervision or collaborative work).
Anthology ID:
2021.ltedi-1.1
Volume:
Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion
Month:
April
Year:
2021
Address:
Kyiv
Venues:
EACL | LTEDI
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–6
Language:
URL:
https://aclanthology.org/2021.ltedi-1.1
DOI:
Bibkey:
Cite (ACL):
Christine Basta and Marta R. Costa-jussa. 2021. Impact of COVID-19 in Natural Language Processing Publications: a Disaggregated Study in Gender, Contribution and Experience. In Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, pages 1–6, Kyiv. Association for Computational Linguistics.
Cite (Informal):
Impact of COVID-19 in Natural Language Processing Publications: a Disaggregated Study in Gender, Contribution and Experience (Basta & Costa-jussa, LTEDI 2021)
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PDF:
https://aclanthology.org/2021.ltedi-1.1.pdf