Summary of Prompt Design Matters For Computational Social Science Tasks but in Unpredictable Ways, by Shubham Atreja et al.
Prompt Design Matters for Computational Social Science Tasks but in Unpredictable Ways
by Shubham Atreja, Joshua Ashkinaze, Lingyao Li, Julia Mendelsohn, Libby Hemphill
First submitted to arxiv on: 17 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research paper investigates how prompt design affects Large Language Models’ (LLMs) ability to perform computational social science tasks such as annotation. The study uses a multi-prompt experiment with three LLM models and four tasks, exploring factors like definition inclusion, output type, explanation, and prompt length. The findings show that LLM compliance and accuracy are highly dependent on prompt design, with significant differences observed between prompts. For instance, using numerical scores instead of labels reduces all LLMs’ performance. Task-dependent optimal prompting setups are identified, highlighting the importance of considering prompt design in LLM-based annotation tasks. The study serves as both a warning and practical guide for researchers and practitioners. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper explores how to get computers to do social science tasks without being taught. Researchers used special language models that can understand text to see if they could perform these tasks well. They tested different ways of asking the models questions, like using numbers or words. The results show that how you ask the question matters a lot! If you use numbers, the model won’t do as well. This study helps us understand what makes computers good at social science tasks and gives us tips on how to make them better. |
Keywords
» Artificial intelligence » Prompt » Prompting
