Visual Gender Stereotypes (Advertisement, Social Media)




gender expressions, gender stereotypes, visual communication, sefies, advertisement


The depiction of gender is the focus of a growing number of content analyses in the fields of both mass media (e.g., Goffman, 1979; Grau & Zotos, 2016; Mitchell & McKinnon, 2019; Sink & Mastro, 2017; Ward & Grower, 2020) and social media (e.g., Baker & Walsh, 2018; Döring, 2019; Döring & Mohseni, 2019; Döring et al., 2016). Typically, the depiction of gender follows traditional gender roles and, hence, does not include at lot of individuality and diversity but sticks to established gender stereotypes (Collins, 2011). Gender steoreotypes are defined as beliefs about how men versus women are (descriptive beliefs) or should be (prescriptive beliefs). Relevant dimensions of gender stereotyping are occupations (e.g., the man as the hero, breadwinner, or executive; the woman as the mother, housewife, or subordinate), sexual and romantic behaviors (e.g., the man seeking sex; the woman seeking love), personality traits (e.g., the man being active, aggressive, rational, and instrumental; the woman being passive, affectionate, emotional, and social), or body types (e.g., the man being tall, muscular and older; the woman being petite, slim, and younger). Gender stereotypes in the media cover different dimensions of traditional masculinity and feminity and are represented textually and/or (audio-)visually. Typically, the occurrence and nature of gender stereotyping in different media is measured and changes over time are of particular interest (e.g., Bhatia & Bhatia, 2020; Maker & Childs, 2003).


Field of application/theoretical foundation:

According to the Social Cognitive Theory (SCT; Bandura 1986, 2009), gender-stereotyped protagonists in the media can influence how media audiences perceive gender roles and to which degree they imitate them as role models. Cultivation theory (Gerbner & Gross, 1976; Kim & Lowry, 2005) predicts, that exposure to distorted media images of reality will shape the audiences’ worldviews. Repeated or constant exposure to gender stereotpyes in the media, according to cultivation theory, will influence the audiences’ perceptions of the roles of women and men in society. Against the background of human rights and gender equality, exaggerated gender stereotypes and the related subordination of women in the media are criticized (e.g. Döring et al., 2016; Goffman, 1979; Grau & Zotos, 2016). Often times, gender-related media content analyses support feminist claims about gender-based inequalities (Collins, 2011; Rudy et al., 2010).

When criticizing gender steoreotypes in the media, it is important to realize, though, that media do not one-directionally influence public perception and opinion (mold theory) but also bi-directionally reflect existing social gender relations and societal attitudes (mirror theory). Last but not least, based on an understanding of stereotypes as cognitive shortcuts and simplifications (Windels, 2016) it needs to be acknowledged that using stereotypes in media representations makes it easier to disseminate clear messages, inform or entertain the audience. Hence, the use of gender-related or other group-related stereotypes is not only an issue of societal relations and equality but also an issue of information processing and message creation.


References/combination with other methods of data collection:

Manual (e.g., Döring et al., 2016) and computational (e.g., Bhatia & Bhatia, 2020) content analyses of gender representations in mass media and social media can be combined. Furthermore, content analyses can be complemented with qualitative interviews and quantitative surveys to investigate both media creators’ and media audiences’ perceptions and evaluations of gender stereotypes in the media. Additionally, experimental studies are helpful to measure directly how different gender stereotypes in the media are perceived and evaluated by recipients and if and how they can affect their gender-related thoughts, feelings, and behaviors (Bast et al., 2021).


Example Studies for Manual Content Analyses:

Acknowledging the multidimensionality and complexity of gender stereotypes in the media, this DOCA entry focuses on the analysis of gender displays in the tradition of Erving Goffman (1979, 1988). Goffman’s approach originally addressed press adversitements and was qualitative in nature. It has been adopted for quantitative content analyses and extended regarding relevant dimensions with a focus on press advertisments (Kang, 1997), magazine titles (Mortensen et al., 2020) as well as social media images such as selfies on Instagram (Döring et al., 2016; Baker & Walsh, 2018). Extending Goffman’s gender display framework to social media contexts and user-generated content does make sense from a theoretical point of view (Butkowski, 2020). Usually, dichotomous or polytomous variables are used to code stereotypical gender displays in the Goffman tradition, however, some content researchers also have developed and used rating scales for coding (Butkowski et al., 2020). So far, published codebooks with example pictures are scarce.

Table 1. Example studies for manual content analyses.

Coding Material Measure Operationalization (excerpt)  Reliability Source

a)     Six categories of gender display according to Goffman (1979, 1988)



Relative size
(between 2 or more persons)

One person (usually the man) is depicted as larger in height and greater in girth through positioning or perspective of the image compared to the other person(s) (usually the woman). Can only be coded with 2 or more persons in the picture. Binary coding (1: yes; 2: no).

Not available


N=500 selfies on Instagram

Feminine touch

One person (usually the woman) is pictured using their fingers and hands to trace the outlines of an object or to cradle it or to caress its surface or to touch their own body (e.g., their hair). The so-called feminine touch is not goal-oriented or functional. Binary coding (1: yes; 2: no).
Example image for femine touch:

Cohen’s Kappa = .79

Döring et al. (2016)


Function ranking
(between 2 or more persons)

One person (usually the man) is pictured in the executive or dominant role, the other person in the subordinate or assisting role (usually the woman). Can only be coded with 2 or more persons in the picture. Binary coding (1: yes; 2: no)

Not available



(nuclear family of four persons)

The typical nuclear family is depicted with mother, father, daughter, and son. Typically, closer bonds between mother and daughter on the one side, and father and son on the other side are depicted. Can only be coded with a whole family in the picture. Multidimensional qualitative variable that has not been adopted for quantitative coding yet.

Not available


N=500 selfies on Instagram

Ritualization of subordination

One person (usually the woman) is depicted in a posture of subordination that deviates from a stable, upright position and includes lying/sitting postures and imbalance.

  • Posture of subordination includes lying or sitting versus standing: Polytomous coding (1: lying, 2: sitting, 3: standing)
    Example image for lying posture:

  • Imbalance in body posture includes canting positions and knee bending. Binary coding (1: yes; 2: no).
    Example image for imbalance posture:

Lying, sitting, standing posture Cohen’s Kappa = 1.00


Imbalance posture: Cohen’s Kappa = .90

Döring et al. (2016)

N=500 selfies on Instagram

Licensed withdrawal

One person (usually the woman) is depicted in a situation of licensed withdrawal meaning that she does not fully turn to the camera. This includes withdrawing gaze and loss of control.

  • Withdrawing gaze means that one person (usually the woman) is depicted gazing away from the camera. Binary coding (1: yes; 2: no).
    Example image withdrawing gaze:

  • Loss of control means that one person (usually the woman) is depicted expressing strong emotions implying that she is not fully focusing on the current scene . Binary coding (1: yes; 2: no).
    Example image loss of control:

Withdrawing gaze: Cohen’s Kappa = 1.00


Loss of control: Cohen’s Kappa = 1.00

Döring et al. (2016)

b)     Two additional gender display categories according to Kang (1997)



N=500 selfies on Instagram

Body Display

Body display of persons vary with the type of clothing.

  • One person (usually the man) is depicted in full clothing. Binary coding (1: yes; 2: no).
  • One person (usually the woman) is depicted in sparse clothing or nudity. Binary coding (1: yes; 2: no).
    Example image sparse closing

Full clothing Cohen’s Kappa = .73


Sparse clothing: Cohen’s Kappa = .73


Döring et al. (2016)


Independence and self-assertiveness

One person (usually the man) is depicted in a position of independence and self-assertivenesss. Binary coding (1: yes; 2: no).

Not available


c)     Three categories of social media related gender stereotypes (Döring et al., 2016)



N=500 selfies on Instagram

Kissing pout

One person (usually the woman) is depicted showing a kissing pout (“duck face”). Binary coding (1: yes; 2: no).

Example image for kissing pout:

Cohen’s Kappa = 1.00

Döring et al. (2016)

N=500 selfies on Instagram

Muscle presentation

One person (usually the man) is depicted presenting their muscles (e.g., biceps, sixpack). Binary coding (1: yes; 2: no).

Example image for muscle presentation:

Cohen’s Kappa = 1.00

Döring et al. (2016)

N=500 selfies on Instagram

Faceless portrayal

One person (usually the woman) is depicted without the face in the picture. Binary coding (1: yes; 2: no).

Example image for faceless portayal:

Cohen’s Kappa = 1.00

Döring et al. (2016)

Note. In order to ensure anonymity, no original Instagram posts are displayed. All example pictures shown are re-enactments to visually illustrate the categories and all protagonists gave their informed consent for publication of the pictures. The pictures are also used in the original study Döring et al. (2016).


The categories of gender display in the tradition of Erving Goffman (1979, 1988) can be complemented with further categories that go into more detail of physical appearance in terms of body type, attire or sexualization. Furthermore, additional dimensions of gender stereotyping such as occupations or activities can be added.



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How to Cite

Döring, N. (2022). Visual Gender Stereotypes (Advertisement, Social Media). DOCA - Database of Variables for Content Analysis, 1(5).



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