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>maybe you've just learned some interesting features of current trends in dating site photos. Again, I hate to keep parroting what another HN said, but I hate

>maybe you've just learned some interesting features of current trends in dating site photos. Again, I hate to keep parroting what another HN said, but I hate to see misinformation repeated: >The paper states that they used an existing net, VGG-Face, to exact facial features: https://osf.io/fk3xr/ https://osf.io/fk3xr/ (page 13) >VGG-Face aims at representing a given face as a vector of scores that are as unaffected as possible by facial expression, background, lighting, head orientation, image properties such as brightness or contrast, and other factors that can vary across different images of the same person. All the heavy lifting for this paper was done by logistic regression on the facial features reported by VGG-Face, they didn't train a DNN specifically for identifying sexuality. The algo wouldn't have seen clothing at all. Basically, it's not as simple as "All the gay participants had rainbow flags in the background of their photo so let's ignore this study"

TFortunato 9y ago
I never said anything about rainbow flags in the background, nor that we should ignore this study. And fine to be pedantic, it wasn't throwing a bunch of photos at a NN classifier, it was throwing a bunch of photos through a NN to get a descriptor of facial features, then training a logistic regression on that. (Note: they did also train a DNN specifically for this, which they used for example to say things like: "Male facial image brightness correlates 0.19 with the probability of being gay, as estimated by the DNN based classifier. While the brightness of the facial image might be driven by many factors, previous research found that testosterone stimulates melanocyte structure and function leading to a darker skin." which some might argue is quite a jump given the data at hand. What I am saying is that the authors may have been a bit far-reaching in their conclusions, and that "trends in dating site photos" doesn't just mean "is there a rainbow flag present?", but also things like how photos are taken w.r.t angles, and lighting, and retouched, makeup, expressions, etc. (and yes VGG-Face is supposed to be resilient to some of these things, they also used Face++ for studies having to do with morphology, such as using facial contour features. But saying they are resilient to these things and quantifying that are two very different things). To get to even a more fundamental question - Does the population of gay and straight individuals on a dating website necessarily reflect the gay and/or straight populations as a whole? And once the authors start talking about the femininity or masculinity of faces, and whether certain features are gender atypical or not, they are entering very murky and ill-defined territory, which the authors even acknowledged when relating previous results on this front. To be very clear about it: I am not saying that the study should be ignored completely, or that there were no interesting findings. Quite the contrary! What I am saying is that the conclusions being reached ("Our results provide strong support for the PHT, which argues that same gender sexual orientation stems from the underexposure of male fetuses and overexposure of female fetuses to prenatal androgen responsible for the sexual differentiation of faces, preferences, and behavior") are quite a bit of a leap from what was found in the research given the input data and methods, and I think should have been more accurately reported as: "interesting differences in social media photographs of gay vs straight individuals.", with a little less speculation by the authors on what might be causing these differences.
- AstralStorm 9y ago
  Note: I haven't yet read that paper. Funny thing though is R=0.19 being used as evidence. First of all, effect size is what matters. Second, this is near zero and essentially worthless. Third, they didn't really check how their methods work or know why they work, just guess. For fun, let's see how easily you can make someone gay with evolutionary approach used in the 2015 fooling face detectors paper. The algorithms are in opencv_contrib. I bet it is essentially worthless.

TFortunato 9y ago

I never said anything about rainbow flags in the background, nor that we should ignore this study. And fine to be pedantic, it wasn't throwing a bunch of photos at a NN classifier, it was throwing a bunch of photos through a NN to get a descriptor of facial features, then training a logistic regression on that. (Note: they did also train a DNN specifically for this, which they used for example to say things like: "Male facial image brightness correlates 0.19 with the probability of being gay, as estimated by the DNN based classifier. While the brightness of the facial image might be driven by many factors, previous research found that testosterone stimulates melanocyte structure and function leading to a darker skin." which some might argue is quite a jump given the data at hand. What I am saying is that the authors may have been a bit far-reaching in their conclusions, and that "trends in dating site photos" doesn't just mean "is there a rainbow flag present?", but also things like how photos are taken w.r.t angles, and lighting, and retouched, makeup, expressions, etc. (and yes VGG-Face is supposed to be resilient to some of these things, they also used Face++ for studies having to do with morphology, such as using facial contour features. But saying they are resilient to these things and quantifying that are two very different things). To get to even a more fundamental question - Does the population of gay and straight individuals on a dating website necessarily reflect the gay and/or straight populations as a whole? And once the authors start talking about the femininity or masculinity of faces, and whether certain features are gender atypical or not, they are entering very murky and ill-defined territory, which the authors even acknowledged when relating previous results on this front. To be very clear about it: I am not saying that the study should be ignored completely, or that there were no interesting findings. Quite the contrary! What I am saying is that the conclusions being reached ("Our results provide strong support for the PHT, which argues that same gender sexual orientation stems from the underexposure of male fetuses and overexposure of female fetuses to prenatal androgen responsible for the sexual differentiation of faces, preferences, and behavior") are quite a bit of a leap from what was found in the research given the input data and methods, and I think should have been more accurately reported as: "interesting differences in social media photographs of gay vs straight individuals.", with a little less speculation by the authors on what might be causing these differences.

AstralStorm 9y ago
Note: I haven't yet read that paper. Funny thing though is R=0.19 being used as evidence. First of all, effect size is what matters. Second, this is near zero and essentially worthless. Third, they didn't really check how their methods work or know why they work, just guess. For fun, let's see how easily you can make someone gay with evolutionary approach used in the 2015 fooling face detectors paper. The algorithms are in opencv_contrib. I bet it is essentially worthless.