Partner perceptions during brief online interactions shape partner selection and cooperation
Tiffany Matej Hrkalovic (Vrije Universiteit Amsterdam, TU Delft - Pattern Recognition and Bioinformatics)
B.J.W. Dudzik (TU Delft - Pattern Recognition and Bioinformatics)
Hayley Hung (TU Delft - Pattern Recognition and Bioinformatics)
Daniel Balliet (Vrije Universiteit Amsterdam)
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Abstract
Evolutionary theory suggests that partner selection – the ability to identify and prefer-entially interact with individuals willing (warmth) and able (competence) to work towards mutual benefits – is a key driver of cooperative behavior. However, partner selection is complex, requiring the integration of various information, such as impression formation and task affordances. Despite its importance, there is limited research on the effect of these factors on partner selection for cooperative tasks. Thus, this paper investigates how person perceptions (warmth and competence), task affordances, and facial and acoustic nonverbal behavior inform partner selection for cooperative tasks. For this purpose, we asked participants to select partners for a task that either expressed warmth- or competence-related traits. Participants had a 3-minute (online) conversation with up to five individuals, reported their evaluations, selected partners for the task, and then engaged in the task. Results indicate that person perceptions guide partner selection, with each trait being more predictive in relevant tasks. Additionally, we found that the perceptions of warmth, but not competence, can be predicted by facial and acoustic cues during con¬versations. Lastly, we find that in the context of online social interactions, individuals were more cooperative towards selected participants than unselected. We discuss these impli¬cations in the context of the theory of partner selection and offer insights on how these results can be used in future efforts for designing socially intelligent artificial systems that support partner selection decisions.
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