We examined whether, even at zero acquaintance, observers accurately infer others’ social network positions—specifically, the number and patterning of social ties (e.g., brokerage—the extent to which a person bridges disconnected people) and the trait impressions that support this accuracy. We paired social network data ( n = 272 professional school students), with naive observers’ ( n = 301 undergraduates) judgments of facial images of each person within the network. Results revealed that observers’ judgments of targets’ number of friends were predicted by the actual number of people who considered the target a friend (in-degree centrality) and that perceived brokerage was significantly predicted by targets’ actual brokerage. Lens models revealed that targets’ perceived attractiveness, dominance, warmth, competence, and trustworthiness supported this accuracy, with attractiveness and warmth most associated with perceptions of popularity and brokerage. Overall, we demonstrate accuracy in naive observers’ judgments of social network position and the trait impressions supporting these inferences.
more »
« less
Exploring the Representational Structure of Trait Knowledge Using Perceived Similarity Judgments
A large body of past work has sought to identify the underlying dimensions that capture our trait knowledge of other people. However, the importance of particular traits in determining our overall impressions of others is not well understood, and different traits may be fundamental for impressions of famous versus unfamiliar people. For instance, we may focus on competence when evaluating a famous person, but on trustworthiness when evaluating a stranger. To examine the structure of overall impressions of famous people and of unfamiliar people, we probed the contributions of 13 different trait judgments to perceived similarity judgments. We found that different sets of traits best predicted perceived similarity between famous people versus between unfamiliar people; however, the relationship between each trait and perceived similarity generalized to some extent from famous people to unfamiliar people, suggesting a degree of overlap in the structure of overall impressions.
more »
« less
- Award ID(s):
- 1943862
- PAR ID:
- 10387316
- Date Published:
- Journal Name:
- Social Cognition
- Volume:
- 40
- Issue:
- 6
- ISSN:
- 0278-016X
- Page Range / eLocation ID:
- 549 to 579
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
When seeing a face, people form judgments of perceptually ambiguous social categories (PASCs), for example, gun-owners, gay people, or alcoholics. Previous research has assumed that PASC judgments arise from the statistical learning of facial features in social encounters. We propose, instead, that perceivers associate facial features with traits (e.g., extroverted) and then infer PASC membership via learned stereotype associations with those traits. Across three studies, we show that when any PASC is more stereotypically associated with a trait (e.g., alcoholics = extroverted), perceivers are more likely to infer PASC membership from faces conveying that trait (Study 1). Furthermore, we demonstrate that individual differences in trait–PASC stereotypes predict face-based judgments of PASC membership (Study 2) and have a causal role in these judgments (Study 3). Together, our findings imply that people can form any number of PASC judgments from facial appearance alone by drawing on their learned social–conceptual associations.more » « less
-
Initial impressions of others based on facial appearances are often inaccurate yet can lead to dire outcomes. Across four studies, adult participants underwent a counterstereotype training to reduce their reliance on facial appearance in consequential social judgments of White male faces. In Studies 1 and 2, trustworthiness and sentencing judgments among control participants predicted whether real-world inmates were sentenced to death versus life in prison, but these relationships were diminished among trained participants. In Study 3, a sequential priming paradigm demonstrated that the training was able to abolish the relationship between even automatically and implicitly perceived trustworthiness and the inmates’ life-or-death sentences. Study 4 extended these results to realistic decision-making, showing that training reduced the impact of facial trustworthiness on sentencing decisions even in the presence of decision-relevant information. Overall, our findings suggest that a counterstereotype intervention can mitigate the potentially harmful effects of relying on facial appearance in consequential social judgments.more » « less
-
From a glimpse of a face, people form trait impressions that operate as facial stereotypes, which are largely inaccurate yet nevertheless drive social behavior. Behavioral studies have long pointed to dimensions of trustworthiness and dominance that are thought to underlie face impressions due to their evolutionarily adaptive nature. Using human neuroimaging (N = 26, 19 female, 7 male), we identify a two-dimensional representation of faces’ inferred traits in the middle temporal gyrus (MTG), a region involved in domain-general conceptual processing including the activation of social concepts. The similarity of neural-response patterns for any given pair of faces in the bilateral MTG was predicted by their proximity in trustworthiness–dominance space, an effect that could not be explained by mere visual similarity. This MTG trait-space representation occurred automatically, was relatively invariant across participants, and did not depend on the explicit endorsement of face impressions (i.e., beliefs that face impressions are valid and accurate). In contrast, regions involved in high-level social reasoning (the bilateral temporoparietal junction and posterior superior temporal sulcus; TPJ–pSTS) and entity-specific social knowledge (the left anterior temporal lobe; ATL) also exhibited this trait-space representation but only among participants who explicitly endorsed forming these impressions. Together, the findings identify a two-dimensional neural representation of face impressions and suggest that multiple implicit and explicit mechanisms give rise to biases based on facial appearance. While the MTG implicitly represents a multidimensional trait space for faces, the TPJ–pSTS and ATL are involved in the explicit application of this trait space for social evaluation and behavior.more » « less
-
Abstract Well-studied techniques that enhance diversity in early design concept generation require effective metrics for evaluating human-perceived similarity between ideas. Recent work suggests collecting triplet comparisons between designs directly from human raters and using those triplets to form an embedding where similarity is expressed as a Euclidean distance. While effective at modeling human-perceived similarity judgments, these methods are expensive and require a large number of triplets to be hand-labeled. However, what if there were a way to use AI to replicate the human similarity judgments captured in triplet embedding methods? In this paper, we explore the potential for pretrained Large Language Models (LLMs) to be used in this context. Using a dataset of crowdsourced text descriptions written about engineering design sketches, we generate LLM embeddings and compare them to an embedding created from human-provided triplets of those same sketches. From these embeddings, we can use Euclidean distances to describe areas where human perception and LLM perception disagree regarding design similarity. We then implement this same procedure but with descriptions written from a template that attempts to isolate a particular modality of a design (i.e., functions, behaviors, structures). By comparing the templated description embeddings to both the triplet-generated and pre-template LLM embeddings, we identify ways of describing designs such that LLM and human similarity perception better agree. We use these results to better understand how humans and LLMs interpret similarity in engineering designs.more » « less
An official website of the United States government

