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

arXiv: https://arxiv.org/abs/2307.04280 · HTML: https://mlsanity.com/paper/2307.04280/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jul 2023.

## Built on by (most cited first, 14 of 14)

- [Emergent social conventions and collective bias in LLM populations](https://mlsanity.com/paper/2410.08948/) (2024)
- [Rehearsal: Simulating Conflict to Teach Conflict Resolution](https://mlsanity.com/paper/2309.12309/) (2023)
- [Simulating Public Administration Crisis: A Novel Generative Agent-Based Simulation System to Lower Technology Barriers in Social Science Research](https://mlsanity.com/paper/2311.06957/) (2023)
- [The Order Effect: Investigating Prompt Sensitivity to Input Order in LLMs](https://mlsanity.com/paper/2502.04134/) (2025)
- [Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review](https://mlsanity.com/paper/2501.12557/) (2025)
- [A Survey on Human-Centric LLMs](https://mlsanity.com/paper/2411.14491/) (2024)
- [From Prompt Engineering to Prompt Science With Human in the Loop](https://mlsanity.com/paper/2401.04122/) (2024)
- [LLMAuditor: A Framework for Auditing Large Language Models Using Human-in-the-Loop](https://mlsanity.com/paper/2402.09346/) (2024)
- [Reflections on Inductive Thematic Saturation as a potential metric for measuring the validity of an inductive Thematic Analysis with LLMs](https://mlsanity.com/paper/2401.03239/) (2024)
- [Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agents](https://mlsanity.com/paper/2310.15065/) (2023)
- [I Am Not Them: Fluid Identities and Persistent Out-group Bias in Large Language Models](https://mlsanity.com/paper/2402.10436/) (2024)
- [Harnessing LLMs for Automated Video Content Analysis: An Exploratory Workflow of Short Videos on Depression](https://mlsanity.com/paper/2406.19528/) (2024)
- [Supporters and Skeptics: LLM-based Analysis of Engagement with Mental Health (Mis)Information Content on Video-sharing Platforms](https://mlsanity.com/paper/2407.02662/) (2024)
- [A Framework for Collaborating a Large Language Model Tool in Brainstorming for Triggering Creative Thoughts](https://mlsanity.com/paper/2410.11877/) (2024)

## Abstract (arXiv)

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.