Capitulo I V: Presentación e Interpretación de Resultados
Categoría 4: “Practicas Intencionadas de Autocuidado”
usion
We have seen that the search results returned differ a lot for search engine used, but also for different search terms for the same search engine. Every search engine seems to have a certain way to rank its permanent features and alternate between the various transient features. These differences also show
29 Original text: ‘女人味是指女人所独有的魅力和吸引力，是女人温柔、优雅、善良、智慧、独立的魅力
the different reality being constructed by the search engine and thus the different discourses or representations of and on gender.
By just using these simple search terms, there was already a whole bunch of eroticized, sexist and even homophobe and homoerotic content (of Baidu). In general, the women terms and especially ‘meinü’ returned most explicit and sexist material, with the very sexual ‘little games’. ‘shuaige’ also appeared in many instances in a very sexualized way but still less than ‘meinü’, where the ideal ‘meinü’ according to Baidu has long beautiful legs and an f-cup. For the men a discourse is created of the strong man that has to perform (also sexually) and be successful, and take good care of his woman.
5.3
Ima
ges
In this part of the analysis, different sets of images of the different searches for the ‘gendered terms’ will be analyzed using a content analysis based on variables Bell (2001) used in his study. Jewitt and Oyama’s (2001) social semiotic approach will also be used as example. To better fit the data, I will complement with more variables, specific to the images that will be analyzed here. The images used in the analysis can be found in the appendix.
5.3.1 Varia
bles
Following Bell (2001), the images will be analyzed based on the variables social distance, visual modality, behavior or contact, and judged age ranges. These I complement with ‘race’ and ‘level of undress’. These variables will be put into a number of different values as to be able to quantify them for analysis.
For social distance, following Jewitt and Oyama (2001: 146), I use the shots frame sizes: close-up, medium shot, and long shot. They respectively stand for an intimate/personal relationship, a social relationship and an impersonal one. I add one value of the ‘selfie’, which counts as a close-up but is still different as it is taken by the participant of the picture him- or herself and thus appears even
closer than the close-up. This can also be a measure for professionality of the picture as a ‘selfie’ points to a regular, amateur internet or social media user.30
For visual modality, following Bell (2001: 30), I use the values low modality, which means a monochrome picture that thus appears less naturalistic, and high modality, where the highly saturated colors make the picture seem more naturalistic. To these I add Jewitt and Oyama’s (2001: 151-2) ‘sensory modality’ which uses very highly saturated colors to make the picture appear ‘more than real’.
For behavior or contact, following Bell (2001: 30-1), I use five values consisting of: offer/ideal (where ‘the model depicted offers herself/himself as an idealized exemplar of a class or attribute, looking away from the viewer’), demand/affiliation (or equality, where the ‘model looks at the viewer, directly, smiling’), demand/submission (where the ‘model looks down at the viewer, not smiling’), demand/seduction (where the ‘model looks up at the viewer, head canted, smiling or “pouting”’), or none of the above.
Judged age ranges is trickier to judge so Bell (ibid.: 33) recommends to just use two values: ‘less than’ and ‘more than’ 25. I also add one ‘unidentifiable’ for when the picture is unclear or framed in a certain way that it becomes impossible to judge the age of the participant. For the variable race, I use four values: Asian, white, other and an ‘unidentifiable’. For the variable ‘level of undress’, as this is also difficult to judge, I will use three values: clothed, ‘half-clothed’, meaning a lot of ‘skin’ is shown like cleavage, the torso or the legs (underneath a short skirt for example), or ‘in state of undress’, meaning in bikini or lingerie, naked or the like. Only the images ‘above the fold’ will be used so that is an average of 13 images for Baidu per query, 10 for ChinaSo, and 20 for Google.
Table 1 Variables for content analysis with different values.
Variable Value 1 Social distance 1.1 selfie
1.2 close-up 1.3 medium shot 1.4 long shot
2 Visual modality 2.1 sensory modality 2.2 high modality 2.3 low modality 3 Behavior or contact 3.1 offer/ideal
3.2 demand/affiliation 3.3 demand/submission 3.4 demand/seduction 3.5 other
4 Judged age range 4.1 above 25 4.2 below 25 4.3 unidentifiable 5 Race 5.1 Asian 5.2 white 5.3 other 5.4 unidentifiable 6 Stage of undress 6.1 fully clothed
6.2 half-clothed 6.3 in state of undress
5.3.2 Conte nt analysis
Before starting the analysis it is important to note that, when querying for these ‘gendered terms’ the images are expected to a priori to display aconceptual structure where the participant of the picture does not perform any action, as was the case for certain queries in part one of the analysis. There were no advertisements among the returned images and the couple of cartoon images that were returned were used in the analysis if possible.
Different than for the vertical rows of image in the first part of the analysis, ChinaSo’s images here used horizontal rows. For Baidu’s images of the queries ‘nüren’ and ‘meinü’, the pictures were bigger in compared to the male queries (so there were less pictures per page) and the pictures linked to collections of photographs, often of girls in sexy clothing or lingerie. The queries in Baidu for ‘nüren’ and ‘meinü’ also returned some of the same pictures.
Table 2 Relative frequency of results content analysis.
Baidu ChinaSo Google HK
‘nan’ ‘nü’ ‘sg’ ‘mn’ ‘nan’ ‘nü’ ‘sg’ ‘mn’ ‘nan’ ‘nü’ ‘sg’ ‘n’ 1.1 0,00 0,00 0,39 0,00 0,00 0,00 0,55 0,00 0,00 0,00 0,72 0,06 1.2 0,64 0,07 0,17 0,08 0,20 0,25 0,18 0,38 0,60 0,67 0,16 0,28 1.3 0,29 0,64 0,39 0,77 0,40 0,25 0,27 0,50 0,40 0,28 0,12 0,50 1.4 0,07 0,29 0,04 0,15 0,40 0,50 0,00 0,13 0,00 0,06 0,00 0,17 2.1 0,79 1,00 0,26 1,00 0,10 0,38 0,18 0,00 0,10 0,39 0,08 0,22 2.2 0,14 0,00 0,70 0,00 0,70 0,50 0,55 0,50 0,75 0,44 0,92 0,78 2.3 0,07 0,00 0,04 0,00 0,20 0,13 0,27 0,50 0,15 0,17 0,00 0,00 3.1 0,29 0,14 0,09 0,08 0,30 0,50 0,36 0,13 0,15 0,06 0,04 0,00 3.2 0,29 0,21 0,30 0,08 0,30 0,13 0,09 0,25 0,10 0,22 0,08 0,17 3.3 0,00 0,29 0,09 0,46 0,00 0,13 0,36 0,38 0,05 0,17 0,16 0,33 3.4 0,14 0,36 0,39 0,38 0,10 0,13 0,18 0,13 0,60 0,50 0,64 0,44 3.5 0,29 0,00 0,13 0,00 0,30 0,13 0,00 0,13 0,10 0,06 0,08 0,06 4.1 0,36 0,00 0,13 0,00 0,80 0,50 0,09 0,25 0,90 0,28 0,00 0,11 4.2 0,21 1,00 0,87 1,00 0,10 0,50 0,91 0,75 0,10 0,72 1,00 0,89 4.3 0,43 0,00 0,00 0,00 0,10 0,00 0,00 0,00 0,00 0,00 0,00 0,00 5.1 0,14 0,79 0,70 1,00 0,30 0,63 0,73 0,75 0,50 0,72 0,92 0,94 5.2 0,79 0,21 0,26 0,00 0,60 0,38 0,27 0,25 0,50 0,28 0,08 0,06 5.3 0,00 0,00 0,04 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 5.4 0,07 0,00 0,00 0,00 0,10 0,00 0,00 0,00 0,00 0,00 0,00 0,00 6.1 0,71 0,29 0,70 0,08 0,67 0,63 1,00 0,63 0,90 0,72 0,96 0,50 6.2 0,00 0,29 0,04 0,31 0,00 0,25 0,00 0,25 0,05 0,22 0,04 0,39 6.3 0,29 0,43 0,26 0,62 0,33 0,13 0,00 0,13 0,05 0,06 0,00 0,11
Social distance it seems doesn’t tell us much about a gender difference as it appears very search engine specific. Long shots seem to be used less frequently. Interesting are the selfies, as they only were used for ‘shuaige’ by all different search engines and in a very high frequency (one exception is the one selfie for Google’s ‘meinü’). The selfie-pictures also have lower modality thus contrasting with many of the pictures of ‘meinü’ and ‘nüren’ who have a high sensory modality as most of them are pictures from more professional photoshoots.
Possible explanation of this could be that the beauty standard for women is overall higher than for men with these pictures reinforcing this, or pictures of attractive women are more in demand than pictures of men so there is an increase in commercialization in the former. The other frequencies in used modality also mirror this with the male being more of a lower, natural standard, and the female a higher standard of for example a magazine cover picture quality. Also, ChinaSo’s images in general appear very old, unlike the high sensory pictures of other search engines.
The behavior also shows a stereotypical image of the women showing much more submissive behavior and the man as the seducer, although the women also showed a lot of seductive looks. The submissive pose is often complemented with a downwards angle so the viewer literally looks down on the participant of the picture. The difference in age that could be reflected in the difference between ‘nanren’ and ‘nüren’ being older than ‘shuaige’ and ‘meinü’, is reflected well by the different search engines for the male queries but not for the female, as for both the queries ‘nüren’ and ‘meinü’, the participants of the pictures look younger than 25 years old. Women over 25 are largely ‘invisible’ on Baidu and Google.
For the variable ‘race’, men were mostly white while women were Asian. Sexualized pictures were ubiquitous for most searches but more for the female terms than the male, and more for ‘meinü’ than ‘nüren’. Baidu seems to offer relatively more sexualized content than the other two search engines, as also for the men it had pictures framed so you only see a (very muscular) body or someone’s crotch in a tight speedo.
5.3.3 Concl usion
There are many different, sometimes contradictory representations of gender given here. They range from ‘racist’ representations, where attractive women are predominantly Asian and handsome or successful men are predominantly white; to many sexist representations, where women should all be young and photo models and men can just be their own manly self (although having a muscular body helps, it is not a necessity).
The different search engines all behave in a very different way with Baidu seemingly being most sexist, also because you can browse further to collections of half-naked women, and ChinaSo least. ChinaSo’s algorithms at times also seems to function properly, with the very outdated pictures it returns and a picture of a girl for the ‘shuaige’ query. The pictures thus imply and naturalize a
6
Con
clusion
This study has tried to show the importance of context and the context-dependence of semiosis (Andersen 1997: 22). Relatively simple and ‘innocent’ addresses like ‘meinü’ and ‘shuaige’ can mean something completely different online for example, as is shown here, than on the street, in a bar, etc. This study clearly showed that online, on the platform of a search engine (and beyond), these
addresses and gender terms in general have meanings ranging from highly sexualized objectifications of gender to the embodiment of certain characteristic such as ‘innocence’ (female) and ‘successful’ (male). The different search engines have all shown here to create and naturalize these discourses on gender.
To sum up, this research has shown that both woman and men are being sexualized online, on the images returned by the search engine, but women significantly more than men. Women are often portrayed as submissive, always young, attractive and Asian, while the men are more often portrayed as the seducers and are more often white. From the set-up of the images and the recommendations, I have shown that women, with the collections of sensual pictures and the sexualized videogames, are much more the object of desire. Although on Baidu there are more glimpses of sexualized men and even homo-erotic material (even though other search results were explicitly anti-homosexual).
My research wants to contribute to ongoing debates and developments in media studies and gender studies and therefore I argue to take the online more into account to learn more about contemporary society. Also, there is need for creative approaches and more understanding of the digital as it will continue to play a bigger part in our everyday lives The content shown and analyzed here is at moments very fragmented, but still it is an important part of how the search engine creates meaning as the analyzed material was all part of the top results and thus receive many visitors.
Through the limitations of the data and of this study, it is difficult to achieve full coverage of the material but this is also not necessary to study representations or discourse being constructed. This has proven to be an interesting analysis but there is need for more context in order to reach a deeper analysis. For future research, it would be interesting to use more digital methods to for example see
where the networks are located of the top results for certain queries, or more multimodal approaches and include for example more homepages.
7
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