How Will I Know if You Really Like Me? Assessing the Role of Appearance, Behavior, and Reciprocity for Meta-Liking Accuracy in Initial Social Encounters | AMiner
How Will I Know if You Really Like Me? Assessing the Role of Appearance, Behavior, and Reciprocity for Meta-Liking Accuracy in Initial Social Encounters
In first social encounters, people regularly try to figure out whether others like them. When accurate, these meta-liking judgments enable individuals to more optimally engage in social interactions. Although previous research shows that people do know how much others like them, little is known about the processes leading to accurate meta-liking judgments. In the present, pre-registered research, we aimed to close this gap by investigating the role of a meta-perceiver’s appearance and behavior, others’ behavior towards that meta-perceiver, and the reciprocity heuristic in forming accurate meta-liking judgments. To this end, we used data from a round-robin study, in which N = 144 participants (Mage = 22.91, 67.6% female) took part in two group meetings, where they interacted with unacquainted others. After each participant had given a short self-introduction, participants indicated liking and meta-liking for each other participant. Additionally, trained raters judged participants’ appearance and behavior during the self-introduction. Results showed that people were able to correctly infer how much others generally liked them but hardly knew how much specific other liked them. Lens model analyses revealed that although one’s appearance and behavior were valid cues for being generally liked, meta-perceivers did not utilize most of these observable cues to inform their meta-liking judgments. However, the assumed reciprocity mediated both individual and dyadic meta-liking accuracy. In light of these findings, we discuss the role of self-observed behavior and stable personality characteristics as well as situational and motivational factors, presenting an integrative theoretical framework to explain generalized and dyadic meta-liking accuracy.