Predicting free-riding in a public goods game : analysis of content and dynamic facial expressions in face-to-face communication / Dmitri Bershadskyy, Ehsan Othman, Frerk Saxen
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Discovery
166588679X
URN
urn:nbn:de:gbv:3:2-107530
DOI
ISBN
ISSN
Autorin / Autor
Beiträger
Körperschaft
Erschienen
Halle (Saale), Germany : Halle Institute for Economic Research (IWH) - Member of the Leibniz Association, [2019]
Umfang
1 Online-Ressource (III, 24 Seiten, 1,6 MB) : Illustrationen, Diagramme
Ausgabevermerk
Sprache
eng
Anmerkungen
Inhaltliche Zusammenfassung
This paper illustrates how audio-visual data from pre-play face-to-face communication can be used to identify groups which contain free-riders in a public goods experiment. It focuses on two channels over which face-to-face communication influences contributions to a public good. Firstly, the contents of the face-to-face communication are investigated by categorising specific strategic information and using simple meta-data. Secondly, a machine-learning approach to analyse facial expressions of the subjects during their communications is implemented. These approaches constitute the first of their kind, analysing content and facial expressions in face-to-face communication aiming to predict the behaviour of the subjects in a public goods game. The analysis shows that verbally mentioning to fully contribute to the public good until the very end and communicating through facial clues reduce the commonly observed end-game behaviour. The length of the face-to-face communication quantified in number of words is further a good measure to predict cooperation behaviour towards the end of the game. The obtained findings provide first insights how a priori available information can be utilised to predict free-riding behaviour in public goods games.
Schriftenreihe
IWH-Diskussionspapiere ; 2019, no. 9 (May 2019) ppn:837399270