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With the recent advances in natural language processing (NLP), a vast numberof applications have emerged across various use cases. Among the plethora ofNLP applications, many academic researchers are motivated to do work that has apositive social impact, in line with the recent initiatives of NLP for SocialGood (NLP4SG). However, it is not always obvious to researchers how theirresearch efforts are tackling today's big social problems. Thus, in this paper,we introduce NLP4SG Papers, a scientific dataset with three associated tasksthat can help identify NLP4SG papers and characterize the NLP4SG landscape by:(1) identifying the papers that address a social problem, (2) mapping them tothe corresponding UN Sustainable Development Goals (SDGs), and (3) identifyingthe task they are solving and the methods they are using. Usingstate-of-the-art NLP models, we address each of these tasks and use them on theentire ACL Anthology, resulting in a visualization workspace that givesresearchers a comprehensive overview of the field of NLP4SG. Our website isavailable at https://nlp4sg.vercel.app. We released our data athttps://huggingface.co/datasets/feradauto/NLP4SGPapers and code athttps://github.com/feradauto/nlp4sg

Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good