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Shaping the Emerging Norms of Using Large Language Models in Social Computing Research

Hong Shen, Tianshi Li, Toby Jia-Jun Li, Joon Sung Park, Diyi Yang

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Abstract

The emergence of Large Language Models (LLMs) has brought both excitement and concerns to social computing research. On the one hand, LLMs offer unprecedented capabilities in analyzing vast amounts of textual data and generating human-like responses, enabling researchers to delve into complex social phenomena. On the other hand, concerns are emerging regarding the validity, privacy, and ethics of the research when LLMs are involved. This SIG aims at offering an open space for social computing researchers who are interested in understanding the impacts of LLMs to discuss their current practices, perspectives, challenges when engaging with LLMs in their everyday work and collectively shaping the emerging norms of using LLMs in social computing research.

Topics & Concepts

Social computingSociologyComputer scienceEngineering ethicsSocial mediaWorld Wide WebEngineeringTopic ModelingRecommender Systems and TechniquesData Quality and Management
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