Open lyashevska opened 10 months ago
Here you can see a list of tags and the number of times they appear.
Examples of stereotypes in online pornography: 1) White women as 'submissive', sexually ‘innocent’ or 'subservient’; a more specific stereotype that falls within this category is that of the ‘Schoolgirl’, another that fits within this frame is the ‘Slut’ stereotype used to denote women who do want to have sex, the ‘Mom’ stereotype may also fall within this category; 2) Men as 'aggressive' and 'dominant’ 3) Asian women as 'exotic’ or ‘innocent’; specific stereotypes that fall within this category are those of the ‘Dragon Lady’ and ‘Lotus Flower’; 4) Black men as ‘overly aggressive’ and endowed with 'a heightened libido' and 'large genitalia’; specific stereotypes that fall within this category are those of the ‘Thug’, ‘Gang’ and ‘BBC’ (Big Black Cock) 5) Black women also as endowed with ‘a heightened libido’ and ‘large bottoms’; a specific stereotype that falls within this category is that of the ‘Jezebel’. 6) Taboo subjects, like ‘incest narratives’; specific stereotypical figures that fall within this category are the ‘stepmom’ and ‘step brother/sister’. 7) White women with very ‘large breasts’ and small waists
Some of the literature I used to come to this list, that may also be interesting to look at in the future:
Looking at the stereotypes above, they can be defined along several axes:
We can make classifiers or scorers that label a video along each of those to get at the stereotypes.
Setting and physical appearance could be broken up in multiple subgroups. Which are necessary? Taboo could be because of the person (stepmom/incest, age) or action (fetishes?) or location (in public / gym / pool)
Appearance has subgroups: length, weight, cupsize, waist, hair color and size.
We see other axis in the data that could be relevant (or not):
@SamiraBohemen can you please look at this?
I think this already looks pretty comprehensive, but I think we at least need to add:
I would say 'specific actions' should also be an axis, I wouldn't map it to the 'setting' axis.
This list seems to be more complete.
Examples of stereotypes in online pornography:
- White women as 'submissive', sexually ‘innocent’ or 'subservient’; a more specific stereotype that falls within this category is that of the ‘Schoolgirl’, another that fits within this frame is the ‘Slut’ stereotype used to denote women who do want to have sex, the ‘Mom’ stereotype may also fall within this category;
- Men as 'aggressive' and 'dominant’
- Asian women as 'exotic’ or ‘innocent’; specific stereotypes that fall within this category are those of the ‘Dragon Lady’ and ‘Lotus Flower’;
- Black men as ‘overly aggressive’ and endowed with 'a heightened libido' and 'large genitalia’; specific stereotypes that fall within this category are those of the ‘Thug’, ‘Gang’ and ‘BBC’ (Big Black Cock)
- Black women also as endowed with ‘a heightened libido’ and ‘large bottoms’; a specific stereotype that falls within this category is that of the ‘Jezebel’.
- Taboo subjects, like ‘incest narratives’; specific stereotypical figures that fall within this category are the ‘stepmom’ and ‘step brother/sister’.
- White women with very ‘large breasts’ and small waists
@SamiraBohemen Can these improve this description?
I use it for word embedding to link descriptions of stereotypes and tags that represent them. The better descriptions, the better results.
We need to shortlist stereotypes of interest (say 10). These will be used together with a list of tags derived from one of the test datasets.