Assessing the point at which averages are stable: A tool illustrated in the context of person perception

Hehman, Eric; Xie, Sally Y; Ofosu, Eugene K; Nespoli, Gabe

doi:10.31234/osf.io/2n6jq

Cited by 56 publications

(55 citation statements)

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“…Furthermore, increasing the number of raters providing attractiveness ratings has a negligible effect on the mean attractiveness ratings once ratings have been collected from 28 raters (Hehman et al, 2018).…”

Section: Facial Attractiveness Ratingsmentioning

confidence: 99%

Comparing theory-driven and data-driven attractiveness models using images of real women’s faces.

Holzleitner¹,

Lee²,

Hahn³

et al. 2019

Journal of Experimental Psychology: Human Perception and Perfor

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Facial attractiveness plays a critical role in social interaction, influencing many different social outcomes. However, the factors that influence facial attractiveness judgments remain relatively poorly understood. Here, we used a sample of 594 young adult female face images to compare the performance of existing theory-driven models of facial attractiveness and a data-driven (i.e., theory-neutral) model. Our data-driven model and a theory-driven model including various traits commonly studied in facial attractiveness research (asymmetry, averageness, sexual dimorphism, body mass index, and representational sparseness) performed similarly well. By contrast, univariate theory-driven models performed relatively poorly. These results (1) highlight the utility of data driven models of facial attractiveness and (2) suggest that theorydriven research on facial attractiveness would benefit from greater adoption of multivariate approaches, rather than the univariate approaches that they currently almost exclusively employ.

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Section: Facial Attractiveness Ratingsmentioning

confidence: 99%

Comparing theory-driven and data-driven attractiveness models using images of real women’s faces.

Holzleitner¹,

Lee²,

Hahn³

et al. 2019

Journal of Experimental Psychology: Human Perception and Perfor

View full text Add to dashboard Cite

show abstract

“…Penton-Voak, Pound, Little, & Perrett, 2006). On average, each photo was rated by 26 participants (Min = 23, Max = 30), which should be sufficient to obtain stable average ratings (Hehman, Xie, Ofosu, & Nespoli, 2018). Participants were unaware that the photos were taken from Airbnb.…”

Section: Photo Ratingsmentioning

confidence: 99%

The effects of facial attractiveness and trustworthiness in online peer-to-peer markets

Jaeger

Sleegers

Evans

et al. 2019

Journal of Economic Psychology

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Online peer-to-peer markets, such as Airbnb, often include profile photos of sellers to reduce anonymity. Ert, Fleischer, and Magen (2016) found that more trustworthy-looking, but not more attractive-looking, Airbnb hosts from Stockholm charge higher prices for similar apartments. This suggests that people are willing to pay more for a night in an apartment if the host looks trustworthy. Here, we present a pre-registered replication testing how photo-based impressions of hosts' attractiveness and trustworthiness influence rental prices. We extend previous investigations by (a) controlling for additional features related to price (e.g., the apartment's location value), (b) testing for an influence of other host features, such as race and facial expression, and (c) analyzing a substantially larger sample of apartments. An analysis of 1,020 listings in New York City showed that more attractive-looking, but not more trustworthylooking, hosts charge higher prices for their apartments. Compared to White hosts, Black (but not Asian) hosts charge lower prices for their apartments. Hosts who smile more intensely in their profile photo charge higher prices. Our results support the general conclusion that people rely on profile photos in online markets, though we find that attractiveness is more important than trustworthiness.

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“…Forty-one participants completed the symmetry Participants completing the masculinity study were students at a university in the United Kingdom, also compensated for their participation with course credit. Recent simulations have shown the number of participants in each condition is sufficient to provide stable average scores [83].…”

Section: Participantsmentioning

confidence: 99%

Biological bases of beauty revisited: The effect of symmetry, averageness, and sexual dimorphism on female facial attractiveness

Jones¹,

Jaeger²

2019

Preprint

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The theoretical factors influencing human female facial attractiveness – symmetry, averageness,and sexual dimorphism – have been extensively studied. However, through improved methodologies, recent studies have called into question their links with life history and evolutionary utility. The current study uses a range of statistical and methodological approaches to quantify how important these factors actually are in perceiving attractiveness, through the use of novel analyses and by addressing methodological weaknesses inherent in the literature. Study One examines how manipulations of symmetry, averageness, femininity, and masculinity affect attractiveness using a two-alternative forced choice task, revealing that increased masculinity is unattractive, but increased femininity is not, and large effects observed for averageness. Study Two utilises a naturalistic ratings paradigm, finding similar effects of averageness and masculinity, but no effects of femininity and symmetry on attractiveness. Study Three applies a random forest machine learning algorithm and geometric measurements of the factors from faces to predict perceived attractiveness, finding that averageness and dimorphism are useful features capable of relatively accurate predictions. However, the factors do not explain as much variance in attractiveness as the wider literature suggests. Implications for future research on attractiveness are discussed.

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Assessing the point at which averages are stable: A tool illustrated in the context of person perception

Cited by 56 publications

References 0 publications

Comparing theory-driven and data-driven attractiveness models using images of real women’s faces.

Comparing theory-driven and data-driven attractiveness models using images of real women’s faces.

The effects of facial attractiveness and trustworthiness in online peer-to-peer markets

Biological bases of beauty revisited: The effect of symmetry, averageness, and sexual dimorphism on female facial attractiveness

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