Are you Awerewolf? Detecting deceptive roles and outcomes in a conversational role-playing game

This paper addresses the task of automatically detecting outcomes of social interaction patterns, using non-verbal audio cues in competitive role-playing games (RPGs). For our experiments, we introduce a new data set which features 3 hours of audio-visual recordings of the popular “Are you a Werewolf?” RPG. Two problems are approached in this paper: Detecting lying or suspicious behavior using non-verbal audio cues in a social context and predicting participants' decisions in a game-day by analyzing speaker turns. Our best classifier exhibits a performance improvement of 87% over the baseline for detecting deceptive roles. Also, we show that speaker turn based features can be used to determine the outcomes in the initial stages of the game, when the group is large.