# The power of moral words: Loaded language generates framing effects in the extreme dictator game

arXiv: https://arxiv.org/abs/1901.02314 · HTML: https://mlsanity.com/paper/1901.02314/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jan 2019.

## Built on by (most cited first, 4 of 4)

- [Social physics in the age of artificial intelligence](https://mlsanity.com/paper/2603.16900/) (2026)
- [Can Global XAI Methods Reveal Injected Behaviours in LLMs? SHAP vs Rule Extraction vs RuleSHAP](https://mlsanity.com/paper/2505.11189/) (2025)
- [Value Alignment Tax: Measuring Value Trade-offs in LLM Alignment](https://mlsanity.com/paper/2602.12134/) (2026)
- [Human behaviour through a LENS: How Linguistic content triggers Emotions and Norms and determines Strategy choices](https://mlsanity.com/paper/2403.15293/) (2024)

## Abstract (arXiv)

Understanding whether preferences are sensitive to the frame has been a major topic of debate in the last decades. For example, several works have explored whether the dictator game in the give frame gives rise to a different rate of pro-sociality than the same game in the take frame, leading to mixed results. Here we contribute to this debate with two experiments. In Study 1 (N=567) we implement an extreme dictator game in which the dictator either gets 0.50 and the recipient gets nothing, or the opposite (i.e., the recipient gets 0.50 and the dictator gets nothing). We experimentally manipulate the words describing the available actions using six terms, from very negative (e.g., stealing) to very positive (e.g., donating) connotations. We find that the rate of pro-sociality is affected by the words used to describe the available actions. In Study 2 (N=221) we ask brand new participants to rate each of the words used in Study 1 from ``extremely wrong'' to ``extremely right'' . We find that these moral judgments explain the framing effect in Study 1. In sum, our studies provide evidence that framing effects in an extreme Dictator game can be generated using morally loaded language.