Good Intentions Beyond ACL: Who Does NLP for Social Good, and Where?
October 06, 2025 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
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Authors
Grace LeFevre, Qingcheng Zeng, Adam Leif, Jason Jewell, Denis Peskoff, Rob Voigt
arXiv ID
2510.04434
Category
cs.CL: Computation & Language
Cross-listed
cs.SI
Citations
0
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
6 months ago
Abstract
The social impact of Natural Language Processing (NLP) is increasingly important, with a rising community focus on initiatives related to NLP for Social Good (NLP4SG). Indeed, in recent years, almost 20% of all papers in the ACL Anthology address topics related to social good as defined by the UN Sustainable Development Goals (Adauto et al., 2023). In this study, we take an author- and venue-level perspective to map the landscape of NLP4SG, quantifying the proportion of work addressing social good concerns both within and beyond the ACL community, by both core ACL contributors and non-ACL authors. With this approach we discover two surprising facts about the landscape of NLP4SG. First, ACL authors are dramatically more likely to do work addressing social good concerns when publishing in venues outside of ACL. Second, the vast majority of publications using NLP techniques to address concerns of social good are done by non-ACL authors in venues outside of ACL. We discuss the implications of these findings on agenda-setting considerations for the ACL community related to NLP4SG.
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