Datensatz

Zusammenfassung

Introduction
Human actions contain an extensive array of socially relevant information. Previous studies have shown that even brief exposure to visually-observed human actions can lead to accurate predictions of goals or intentions accompanying human actions. For example, motion kinematics can enable predicting the success of a basketball shot, or whether a hand movement is carried out with cooperative or competitive
intentions. It has been also reported that gestures accompanying a conversation can serve as a rich source of information for decision making to judge about the trustworthiness of another person. Based on these previous findings we wondered whether humans could actually predict the cooperativeness of another individual by identifying visible social cues. Would it be possible to predict the cooperativeness of a person by just observing everyday actions such as walking or running? Wehypothesized that even brief excerpts of human actions depicted and
presented as biological motion cues (i.e. point-light-figures) would provide sufficient information to predict cooperativeness. Using motion-capture technique and a game-theoretical interaction setup we explored whether prediction of cooperation was possible merely by
observing biological motion cues of everyday actions, and which actions were enabling these predictions.
Methods
We recorded six different human actions—walking, running, greeting, table tennis playing, choreographed dancing (Macarena) and spontaneous dancing—in normal participants using an inertia-based motion capture system. We used motion capture technology (MVN Motion Capture Suit from XSense, Netherlands) to record all actions. A total
number of 12 participants (6 male, 6 female) participated in motion recording. All actions were then post-processed to short movies (ca. 5 s) showing point light stimuli. These actions were then evaluated by 24 other participants in terms of personality traits such as cooperativeness
and trustworthiness, on a Likert scale ranging from 1 to 7. The original participants who provided the recorded actions then returned a few months later to be tested for their actual cooperativeness performance. They were given standard social dilemmas used in game theory such as the give some game, stag hunt game, and public goods game. In those interaction games, they were asked to exchange or give
tokens to another player, and depending on their choices they were able to win or lose an additional amount of money. The choice of behavior for each participant was then recorded and coded for cooperativeness. This cooperativeness performance was then compared with the perceived cooperativeness based on the different ratings of
their actions performed and evaluated by other participants.
Results and Discussion
Preliminary results showed a significant correlation between cooperativeness ratings and actual cooperativeness performance. The actions showing a consistent correlation were Walking, Running and Choreographed Dancing (Macarena). No significant correlation was observed for actions such as Greeting, Table tennis playing or Spontaneous Dancing. A similar tendency was consistently observed across all actions, although no significant correlations were found for
all social dilemmas. The ratings of different actors and actions were highly consistent across different raters and high inter-rater-reliability was achieved. It seems possible that natural and constrained actions carry more social cues enabling prediction of cooperation than actions
showing more variance across different participants. Further studies with higher number of actors and raters are planned to confirm whether accurate prediction of cooperation is really possible.