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Coronagraben in Switzerland: Culture and social distancing in times of COVID-19
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Cognitive Skills, Strategic Sophistication, and Life Outcomes
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Personality Traits, Migration Intentions, and Cultural Distance
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Predicting free-riding in a public goods game: Analysis of content and dynamic facial expressions in face-to-face communication
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Abstract:
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.
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Keyword:
automatic facial expressions recognition; C80; C92; content analysis; D91; ddc:330; face-to-face communication; public goods experiment
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URN:
urn:nbn:de:gbv:3:2-107530
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URL: http://hdl.handle.net/10419/196589
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Cognitive Skills and the Development of Strategic Sophistication
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