Predicting Group Contribution Behaviour in a Public Goods Game from Face-to-Face Communication.

Ehsan Othman,Philipp Werner,Frerk Saxen,Joachim Weimann,Dmitri Bershadskyy,Ayoub Al-Hamadi

doi:10.3390/s19122786

Abstract

Experimental economic laboratories run many studies to test theoretical predictions with actual human behaviour, including public goods games. With this experiment, participants in a group have the option to invest money in a public account or to keep it. All the invested money is multiplied and then evenly distributed. This structure incentivizes free riding, resulting in contributions to the public goods declining over time. Face-to-face Communication (FFC) diminishes free riding and thus positively affects contribution behaviour, but the question of how has remained mostly unknown. In this paper, we investigate two communication channels, aiming to explain what promotes cooperation and discourages free riding. Firstly, the facial expressions of the group in the 3-minute FFC videos are automatically analysed to predict the group behaviour towards the end of the game. The proposed automatic facial expressions analysis approach uses a new group activity descriptor and utilises random forest classification. Secondly, the contents of FFC are investigated by categorising strategy-relevant topics and using meta-data. The results show that it is possible to predict whether the group will fully contribute to the end of the games based on facial expression data from three minutes of FFC, but deeper understanding requires a larger dataset. Facial expression analysis and content analysis found that FFC and talking until the very end had a significant, positive effect on the contributions.

Highlights

Cooperation is one of the major foundations of economic actions
We introduce the following issue to the computer vision and behaviour understanding domain: the prediction and understanding of behaviour based on face-to-face communication (FFC) analysis
We propose an automatic facial expression analysis approach for the prediction of future group behaviour from pre-play

Summary

Introduction

Cooperation is one of the major foundations of economic actions. Given its essential role, a lot of research in economics focuses on how cooperation can be improved. At the heart of this research is the evidence that communication is a highly effective tool to mediate social dilemmas [1]. A very straightforward way to analyse social dilemmas in experimental economics research is to use the public goods game, an experimental setup that allows for cooperation and incentivises free riding. An especially non-intrusive and simultaneously very effective way of doing this is to provide the participants of the experiment with an opportunity to communicate with each other prior to the public goods game itself. This free-form, face-to-face communication (FFC) induces group members to make more socially

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