Good Intentions Beyond ACL: Who Does NLP for Social Good, and Where?

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 agendasetting considerations for the ACL community related to NLP4SG. In this work, we aim to gain a deeper understanding of the broader landscape of NLP4SG by adopting a scientometric approach that examines authors and publication venues (Ni et al., 2013) . We first augment an existing corpus of scientific papers with annotations for whether the work uses NLP techniques, whether the authors have published substantially within ACL, and the venue type (ACL, ACL-ADJACENT, or EXTERNAL; Section 2). Analyzing these data, we find that papers by ACL authors in venues outside of the ACL Anthology are more than three times as likely to address social good topics as those inside it, and that the substantial majority of NLP4SG work takes place beyond ACL by non-ACL authors.