RUNNING HEAD: THE GROUP ATTRACTIVENESS EFFECT
The Group Attractiveness Effect: How does it apply to less attractive groups?
Bachelor thesis
Myrthe van den Kieboom
ANR: 740652
Supervisor: Yvette van Osch
Tilburg University
THE GROUP ATTRACTIVENESS EFFECT
Abstract
This thesis focused on the Group Attractiveness Effect (GA-effect). The GA-effect causes attractive groups to be rated as more attractive than the average physical attractiveness of their members. In addition, previous research indicated that people tend to give groups more
‘extreme’ ratings (both positive as negative) than they would when rating individuals separately.
Hence, an effect occurred for relatively unattractive groups, the group scored lower on attractiveness compared to the average physical attractiveness of their members. In this thesis three groups were tested varying in physical attractiveness and formulated the following hypotheses:
Firstly, there is expected that the high physical attractive group will score higher as a group, than the average of their members (consistent with the GA-effect). Secondly, there is expected that the low physical attractive group will score lower as a group, than the average of their members. The third and final hypothesis is that the effect in the medium physical attractive group will be smaller than the effect in the high and low physical attractive groups.
Participants were asked to provide a rating, based on attractiveness, on female-only group photos, and subsequently rate the individuals in the group separately. A repeated measures
ANOVA revealed results in favour of all three hypotheses.
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THE GROUP ATTRACTIVENESS EFFECT
The Group Attractiveness Effect: How does it apply to less attractive groups?
How our impressions about groups and individuals are formed is more complex than we might expect. Impressions of an individual or a group are formed via the same fundamental information-processing system, however the outcomes can differ (Hamilton & Sherman, 1996).
Previous research has shown that similar behavioural traits result in different impressions of a group versus individuals. Ratings of individuals might differ from group ratings based on what kind a trait is examined (for example physical attractiveness, clothes, language, et cetera). This thesis focuses on the trait physical attractiveness. Physical attractiveness is one important trait, because first impressions and evaluations can be formed based on this feature. However, little is known about how people perceive groups based on physical attractiveness. Therefore, Van Osch,
Blanken, Meijs, and Van Wolferen, (2015) set out to examine this process. The study of Van
Osch, et al. (2015) compared the impressions of groups when rated as a whole, and groups based on the average rate of their individuals. Van Osch, et al. (2015) found that the perceived physical attractiveness of a group is greater than the average physical attractiveness of their members.
They named this effect Group Attractiveness Effect (GA-effect).
However, according to the averaging rule, one expects to judge a groups’ physical attractiveness based on the average attractiveness of its members. Indicating that in rating a group, all members will be taken into account and the impression of the group is the weighted average of the individual scores (Anderson, 1965). Van Osch, et al. (2015) mentioned the averaging rule as the most supported claim for group impressions. However, this is not the case for the physical attractiveness trait in their research. The research showed that the group was rated higher on physical attractiveness than the averaged mean attractiveness of the group members.
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THE GROUP ATTRACTIVENESS EFFECT
Van Osch, et al. (2015) asked participants to rate groups and the individuals of groups separately based on their physical attractiveness. By averaging the scores of the individual group members a group’s mean attractiveness rating was formed to be compared with the group score.
By using within-subject as well as between-subject designs, the GA-effect was found multiple times. For example, in their first study they used a within-subject factor for the five different groups of women they showed the participants, and the between-subject factor as the ratings for the women; group versus individuals. To check whether the presentation of the photos influenced participants in their ratings, the photos were presented in different ways throughout the studies.
For instance, they were presented in isolation, as a cropped photo, with numbers above their faces, and with squares around their faces. Van Osch, et al. (2015) found that it did not matter how the photos were presented, in all cases the GA-effect occurred.
Van Osch, et al. (2015) expected that selective attention is a key driver for the Group
Attractiveness Effect. Selective attention could cause people to pay more attention to the most attractive group members, and take the less attractive members less into account. People spend more time looking at attractive faces, than at less attractive faces. This is consistent with results they found with eye-tracking data and with the “Whom Do You Remember?” study of Van
Osch, et al. (2015). Hence, selective attention suggests that the group rating is skewed towards the more attractive group members.
Earlier research by Willis (1960) tried to find the effect of stimulus pooling on judging attractiveness. This research tried to answer the question on whether the process of responding to composite stimuli by themselves is enough to declare the exaggeration of group differences, as found in social stereotyping. Willis’ (1960) experiments showed participants sets of two or three photos for which they had to rate the average attractiveness. The photos contained relatively
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THE GROUP ATTRACTIVENESS EFFECT attractive and relatively unattractive faces. In his research no faces considered as averagely attractive were used. The sets were systematically varied by set size, mean attractiveness of the set components, heterogeneity, absence of presence of skewness, sex of the photographic subjects. Heterogeneity in this case can be defined as the average deviation of the mean of the set components. Willis used all same sex photographs. Some sets were assembled in subseries, which were sorted by a judge by matching females and males. The subseries, which were all matched by mean attractiveness and heterogeneity, thereby formed three different series. All series were judged by one or two participants together, and they were asked to sort and place each set. Willis (1960) found that the relatively attractive groups were rated as more attractive than the mean attractiveness of the group members, which is in line with the GA-effect. Willis found that for the relatively unattractive groups, that the group was rated as less attractive than the mean attractiveness of the group members. Willis (1960) found these results in the sets of two or three individuals. In addition, increasing the group sizes resulted in more polarized attractiveness ratings of the groups.
As stated above, more research needs to be performed on how physical attractiveness influences people’s impressions on groups and individuals. Willis (1960) already showed that the evaluation of groups was more extreme than the average score of its individual members. Van
Osch, et al. (2015) on their turn found the Group Attractiveness Effect (GA-effect). To contribute to the existing body of research this study combines the findings of the researches of and Willis (1960) and Van Osch, et al. (2015). As shown by the amount of time that passed between these two articles there is still much research to be done.
This study defined three different groups that vary in physical attractiveness, ranging from high to medium and low physical attractiveness. In line with Van Osch, et al. (2015) the
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THE GROUP ATTRACTIVENESS EFFECT study expects to find evidence supporting the GA-effect for the high attractive groups. This research will also include a medium attractive group, which differs from earlier research. Willis
(1960) only used relatively attractive or relatively unattractive groups. Van Osch, et al. (2015) used different groups, they use female, male, and mixed-gender groups, but not groups that varied in attractiveness. Selective attention would suggest that more attention is to be paid towards the more attractive faces, which suggests that the medium attractive group also might score somewhat higher than the average individual score, but the expectancy is not to find significant effects for this group. The third group is the low attractiveness group; An effect is expected in line with Willis’ (1960) findings, that attractiveness of groups is evaluated more extremely than when evaluation its individuals separately. This will indicate a lower group score, than the averaged mean of the individuals. A difference with previous research is that this study used three groups that vary in attractiveness, it only contains all female groups, and the group sizes are larger. Where Willis only used photos of individuals matched together, this study uses real groups of females standing next to each other in the photo.
In sum, research shows that there is a difference in how people rate a group versus how they rate the individuals belonging to that group. An attempt is made to find confirming or disconfirming evidence for the Group Attractiveness Effect (GA-effect). It tries to find if low, medium, and high physical attractiveness influences the way people perceive groups. The first hypothesis is that the high physical attractive group will score higher as a group, than the average of their members. The second hypothesis is the low physical attractive group will score lower as a group, than the average of their members. The third and final hypothesis is that the effect in the medium physical attractive group will be smaller than the effect in the high and low physical attractive groups.
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THE GROUP ATTRACTIVENESS EFFECT
Method
The study investigated the Group Attractiveness Effect (GA-effect). This study compared three different groups that vary in attractiveness. Ratings were collected from the group as a whole and the group members individually.
Participants
In this study 747 Dutch participants participated, 574 completed the survey. The data of only these 574 participants is used. 397 participants were female (69.1%) and 177 were male
(30.9%). Ages were ranged from 18 to 80 years old (Mage = 31.50, SD = 14.06). The participants were obtained through online sampling via social media, via Facebook, LinkedIn, e- mail, forum.fok.nl and forum.scholieren.com. The low condition consisted of N = 199, the medium condition had an N = 192, and the high condition had an N = 183. The survey was active for eleven days from the 7th of November through the 17th of November 2017.
Design
The study had a 2 (Rating: group vs. individual) x 3 (Condition: low vs. medium vs. high) mixed design, with rating as a within subject and condition as a between subject design.
Materials
Pre-test.
First, 42 photos of all women groups were selected from flickr.com, creative commons.
The pre-test selection was made, based on the size of the groups and the position the women were standing in. Two sets of photos were formed, to spread the chance to find more results. The two sets were based on the number of women standing on the photos. The pre-test was done to determine which photos were best to use for the three different low, medium, and high conditions. Ten different photos were tested, set 1 consisted of six different photos and set 2 had
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four photos. A sample of twenty participants was used. The participants were asked to judge ten
group photos (see Appendix for the photos). The ages of the participants of the pre-test varied
from 17 to 60, 45% of the participants were female, 55% were male (Mage = 33.50, SD = 15.03).
The participants rated the groups using a 7-point scale. For all group photos they had to answer
the question “How physically attractive do you find these women” (1 = not at all attractive and 7
= very attractive). Three different photos for both sets 1 tested significantly to form a low,
medium and high attractive group (all p’s < .017). For set 2 three photos differed significantly
and were, therefore, selected to form the three conditions (all p’s < .001). The rest of the photos
were eliminated after testing the results. The results can be found in table 1 and 2.
Table 1: Mean and Standard Deviation of the pre-test of Set 1 N M SD
Foto 1* 20 3.60 .27
Foto 2 20 3.45 .27
Foto 3 20 3.75 .24
Foto 4* 20 3.05 .25
Foto 5* 20 4.65 .26
Foto 6 20 4.50 .30
Table 2: Mean and Standard Deviation of the pre-test of Set 2 N M SD
Foto 1* 20 2.25 .28
Foto 2 20 4.50 .34
Foto 3* 20 3.15 .21
Foto 4* 20 4.65 .25
* photo selected and used for the survey
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Procedure
After analysing the photos best suited for this research, participants were asked to fill in a short online Qualtrics questionnaire that would take about eight minutes of their time. The questionnaire consisted of twenty questions about self-esteem1 and after that, they had to rate photos based on attractiveness. For all photos (group and individual) they had to answer the question “How attractive do you find these women/this woman” (1 = not at all attractive and 7 = very attractive). As mentioned, the questionnaire contained two sets: Set 1 contained three photos with seven females on each photos and set 2 existed of three photos with nine females in the medium and high condition, and ten in the low condition. The participants were randomly assigned to the low, medium or high condition, to avoid sampling bias. They first had to rate the photo of the group in one of the three conditions they were assigned to and then all the individuals in this group (indicated with a red frame around their faces, see figure 1) using the 7- point scale in two different sets. The individual scores were averaged to obtain a mean individual attractiveness rating. After having rated all the photos, participants filled in their age, gender and were offered the opportunity to comment on the questionnaire. Finally, the participants were debriefed and thanked for their participation.
Figure 1. Photograph of the medium condition in set 1 to illustrate how an individual was marked with a red shape.
1 Because the fellow student researcher tried to find self-esteem as a moderator on the GA-effect, the questionnaire consisted of twenty questions about self-esteem. For those questions the State Self-esteem scale by Heatherton and Polivy (1991) was used. The scale contained of three subscales, social -, appearance - and performance self-esteem. 9
THE GROUP ATTRACTIVENESS EFFECT
Results
Main analysis . The main analysis was conducted using a repeated measures ANOVA with a 2 (Rating) x 2 (Set) x 3 (Condition) design, with rating and set as a within-subject factor and condition as a between-subject design. Significant main effects were found: Wilks’ λRating =
.99, F(1, 561) = 5.95, p = .015, η² = .01 and Wilks’ λSet = .96, F(1, 561) = 23.42, p = .00, η² =
.04. These main effects were qualified by two-way interaction. Another significant two way effects were found for the 2 (Rating) x 3 (Condition) design: Wilks’ λ = .82, F(2, 561) = 60.21, p
< .001, η² = .18 and for the 2 (Set) x 3 (Condition) design: Wilks’ λ = .90, F(1, 561) = 29.92, p <
.001, η² = 0.09. These two-way interaction effects were qualified by a three-way interaction effect. The three-way interaction was tested significant for the 2 (Rating) x 2 (Set) x 3
(Condition) design: Wilks’ λ = .96, F(2, 561) = 10.09, p < .001, η² = .03. The three-way interaction did indicate differences between amount of attractiveness across rating and across the two sets. All other effects were tested as not significant. To better explore the results, a repeated measures ANOVA and simple effects analyses were conducted per set.
Set 1. For set 1 a repeated measures ANOVA was conducted, to find effects. A significant interaction effect was found for the 2 (Rating) x 3 (Condition) design: Wilks’ λ = .95,
F(2, 571) = 15.65, p < .001, η² = .05. This shows that in set 1 the rating was different when looking at condition. No other significant effects were found.
After the repeated measures ANOVA simple effects analyses were conducted, the results are illustrated in figure 2. As expected, the group photo in the low condition (M = 3.61, SD =
1.23) was rated less attractive than the average of the individuals (M = 3.80, SD = .91, p = .002, d
= 0.18). For the medium condition there was found that the group photo (M = 3.88, SD = 1.16) did not have an effect by looking at the averaged individuals in the photo (M = 3.86, SD = 1.02,
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THE GROUP ATTRACTIVENESS EFFECT p = .790, d = .02). Finally, in set 1 an effect was found following the GA-effect, the group photo of the women in the high condition (M = 4.74, SD = 1.09) was rated higher than the averaged individual score (M = 4.49, SD = .86, p < .001, d = 0.25). The effect size can be interpreted as a small effect for the low condition, and a small to medium effect for the high condition.
Set 1 7
6
5
4
3
2
1 Low Medium High
Group Individual
Figure 2. Attractiveness ratings per condition for set 1
Set 2. For set 2 another repeated measures ANOVA was conducted, to find effects. A significant main effect for the 2 (Rating) x 3 (Condition) design was found: Wilks’ λ = .98, F(1,
565) = 8.23, p = .004, η² = .01. While looking at a 2 (Rating) x 3 (Condition) design, a significant effect was found; Wilks’ λ = .82, F(2, 565) = 60.22, p < .001, η² = .18. No other significant effects were found.
After the repeated measures ANOVA simple effects analyses were conducted, results are illustrated in figure 3. As expected, in set 2 the group photo in the low condition (M = 3.07, SD =
1.39) was rated less attractive than the average of the individuals (M = 3.37, SD = 1.09, p < .001, d = 0.24). For the medium condition there was found that the group photo (M = 3.96, SD = 1.23)
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THE GROUP ATTRACTIVENESS EFFECT did not have an effect by looking at the averaged individuals in the photo (M = 3.96, SD = 1.03, p = .874, d = 0). Finally, in set 2, an effect was found following the GA-effect, the group photo of the women in the high condition (M = 4.85, SD = 1.09) was rated higher than the averaged individual score (M = 4.26, SD = .89, p < .001, d =0.59). The effect size can be interpreted as a small to medium effect for the low condition, and a medium to high effect for the high condition.
Set 2 7
6
5
4
3
2
1 Low Medium High
Group Individual
Figure 3. Attractiveness ratings per condition for set 2
Discussion
As elaborated in the previous chapter, evidence for the GA-effect was found. People rated the female groups as more attractive than the average of its members. However, this effect only occurred in the high attractive groups. For the medium attractive groups, no significant effect was found. The low attractive group showed a result in line with Willis (1960), namely that this group was rated as less attractive than the average attractiveness of its members when rated separately. This confirms that people tend to rate groups more extremely than simply averaging the attractiveness ratings of the individuals in the group. The effects of the low and the
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THE GROUP ATTRACTIVENESS EFFECT high attractive groups were greater than the effects in the medium attractive groups, thus all the hypotheses were confirmed. The effects in the photos of set 2 were bigger than the effects in the photos of set 1. These results match the results of the pre-test. In set 2 the simple effects were more widely spread, so bigger effects could be expected.
In the sitcom How I Met Your Mother, Barney Stinson, as portrayed by Neil Patrick
Harris, brought a concept called the “Cheerleader Effect” to popular culture. He indicates that a group of women can seem attractive, but only as a group. When you look at each woman individually, it might change your opinion about how attractive they really are (Rashid, &
Fryman, 2008). The cheerleader effect described by Walker and Vul (2014) state that people seem more attractive in a group, than in isolation. Walker and Vul (2014) attribute this to context and contrast effects. When one sees one woman, the rating needs to be based on only this person.
However, when you see a person in a group context, a rating can be based on the whole group, using the group as reference material.
Contrast-effects could have been a limitation in this study. After having conducted the research, there was found that some females were on multiple photos in multiple conditions. In the low condition in set 1, and in the medium condition set 1 and set 2, there were some of the same females in the photos. Looking at the average ratings for those particular individuals, there was a slight difference in the ratings. The individuals were rated higher in the low condition compared to the medium conditions. This could be the successive contrast described by Wedell,
Parducci and Geiselman (1987), who found that the same faces were rated higher when the less attractive faces were dominant in experimental series. In addition, they found the opposite, called the assimilation effect; the same face can be rated as less attractive when they are presented next to a less attractive face. Hence, it seems reasonable to think that the other females in the low
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THE GROUP ATTRACTIVENESS EFFECT attractive condition were less attractive, so the assimilation effect occurs for the females that were on multiple photos that were rated higher in the low condition. It also works the other way around, if those females were presented next to the high attractive females, the other females were probably rated as more attractive, because of the successive contrast effect.
The finding that the GA-effect works mostly through selective attention could be explained when the trait attractiveness is the most salient trait. In this research, participants were asked to rate people only based on their physical attractiveness, so this could be perceived as a salient trait. Maner et al. (2003) previously found what Van Osch, et al. (2015) also found in their study, that people spend more time looking at more attractive females than less attractive females. The most physically remarkable woman or women have a large influence on the evaluation of a group, and the less attractive individuals will be taken less into account while making a group judgement. When a person (or more than one) is perceived as salient, they are seen as more prominent and the perceiver evaluates her as more extreme (Taylor and Fiske,
1987). This effect could clarify why people rate the group photos more extreme than the individual members in the high and low condition. It suggests that in the high and low condition one or more individuals could be seen as salient. In the medium condition the individuals could have contained individuals who were not perceived as salient.
A limitation in this study was that underlying psychological processes could not be investigated in more detail. After this study, only the outcomes of the ratings can be interpreted, but not the psychological processes that occur underneath. Hence, the selective attention account was not tested in this research. This study proves again that people do rate in extremes, however, why people rate in extremes is a question that remains unanswered. Future research could provide more insight in this phenomenon.
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In this thesis in all cases the group photos had to be rated before the individuals. Van
Osch, et al. (2015) found that by letting the participant’s rate the individuals before the group, the effect was smaller. In that study the condition in which the participants scored the group before the individuals the GA-effect was twice as large as in the individuals before group condition. They found that the overall ratings were lower when the participants first rated the individuals. An explanation could be that by rating the group photo before the individuals, participants might (sub-) consciously try to be consistent with their earlier rating when rating the individuals afterwards. Whereas Van Osch, et al. (2015) did not have a low attractive group, impact on reversing the order of rating (individual-group) warrants further research on the low condition.
Another influence on the GA-effect could be cultural accounts. One could suggest that the females that suite the current standards best, are rated better than the ones who do not.
Nowadays in our modern Western world, people are exposed to the media very often. Viewers begin to accept the media portrayals as representation of reality. Throughout time, the standard of women’s beauty has been unrealistic and difficult to attain. Before the 19th century physically strong and fertile woman had preference, but it shifted and women with tiny waists came to be valued (Derenne, & Beresin, 2006). Nowadays the thin ideal women are a normative belief and expected role models (Grabe, Ward, & Hyde, 2008). It makes us focus a lot on appearance
(Lopez-Guimera, Levine, Sanchez-carracedo, & Faquet, 2010). The media is part of our perceiving in what is attractive and what is not. One has the ideal woman in their minds, so they rate the females that most confirm to this image, as more attractive than the ones that do not confirm to their image. The participants for this study were all Dutch, thus they might rate based on what they think is suited best to the Western standards of woman. In, for example, China
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THE GROUP ATTRACTIVENESS EFFECT there could be an other beauty standard. Which suggest when this study, with the same photos, is provided there, other outcomes can be expected. Momentarily, the GA-effect has only been researched in the Netherlands, where the Western standard is perceived as normal. It might seem interesting to see if the GA-effect does occur in other cultures.
Both Van Osch et al. (2015) and this research focused only on testing the GA-effect on humans as the primary subject of research. However, research on the possibility to apply this effect in for instance a product ‘branding’ context could prove interesting. For example; a new product (individual), e.g. Coca Cola, could have a higher rating approval rating just by associating with the Coca Cola brand / product portfolio (group). Even though scarcity always sells, in line with the GA-effect, one can suggest to sell products in groups/bundles to increase rating of product attractiveness.
Lastly, I would like to conclude in the spirit of Nobel Laureate Daniel Kahneman’s self- reflection in his book ‘Thinking, fast and slow’ (2011) who stated:
‘My intuitive thinking is just as prone to overconfidence, extreme predictions, and the planning fallacy as it was before I made a study of these issues. I have improved only in my ability to recognize situations in which errors are likely… And I have made much more progress in recognizing the errors of others than my own.’ (pp. 417)
This thesis’ contributions will be added to the body of research on the Group
Attractiveness Effect. However, this thesis increase in knowledge also increases understanding that additional research is required on the implications and (practical) applications of these findings.
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attractiveness is greater than the average attractiveness of its members the group
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Appendix
Set 1 Low condition
20-10-2016, retrieved from: https://www.flickr.com/photos/elijahrainphoto/17199981708/
Medium condition
20-10-2016, retrieved from: https://www. flickr.com/photos/elijahrainphoto/21233569228/
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High condition
20-10-2016, retrieved from: https://www.flickr.com/photos/smnester/6119136274/in/album- 72157627608637174/
Set 2 Low condition
20-10-2016, retrieved from: https://www.flickr.com/photos/jewishwomensarchive/20829050064/in/album- 72157656354948293/ 20
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Medium condition
20-10-2016, retrieved from: https://www.flickr.com/photos/elijahrainphoto/17385853772/in/album-72157652401382795/
High condition
20-10-2016, retrieved from: https://www.flickr.com/photos/greekatduke/10190940114/in/album-72157644578857411/
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