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Description: This file contains data and analyses for the project with Matjaž Perc under the same title. Abstract: Understanding human behaviour in decision problems and strategic interactions has wide-ranging applications in economics, psychology, and artificial intelli- gence. Game theory offers a robust foundation for this understanding, based on the idea that individuals aim to maximize a utility function. However, the exact factors influencing strategy choices remain elusive. While traditional mod- els try to explain human behaviour as a function of the outcomes of available actions, recent experimental research reveals that linguistic content significantly impacts decision-making, thus prompting a paradigm shift from outcome-based to language-based utility functions. This shift is more urgent than ever, given the advancement of generative AI, which has the potential to support humans in mak- ing critical decisions through language-based interactions. We propose sentiment analysis as a fundamental tool for this shift and take an initial step by analyzing 61 experimental instructions from the dictator game, an economic game captur- ing the balance between self-interest and the interest of others, which is at the core of many social interactions. Our meta-analysis shows that sentiment analy- sis can explain human behaviour beyond economic outcomes. We discuss future research directions. We hope this work sets the stage for a novel game theoretical approach that emphasizes the importance of language in human decisions.