Deep tags: toward a quantitative analysis of online pornography

Abstract

The development of the web has increased the diversity of pornographic content, and at the same time the rise of online platforms has initiated a new trend of quantitative research that makes possible the analysis of data on an unprecedented scale. This paper explores the application of a quantitative approach to publicly available data collected from pornographic websites. Several analyses are applied to these digital traces with a focus on keywords describing videos and their underlying categorization systems. The analysis of a large network of tags shows that the accumulation of categories does not separate scripts from each other, but instead draws a multitude of significant paths between fuzzy categories. The datasets and tools we describe have been made publicly available for further study.

Keywords:

• online pornography
• computational social sciences
• sexual categories
• network analysis

Notes

1. http://www.alexa.com/topsites/category/Top/Adult. Accessed August 27, 2013.

2. Alexa and Netcraft rankings, accessed in August 2013.

3. http://pornstudies.sexualitics.org/#datasets. Accessed August 28, 2013.

4. https://creativecommons.org/licenses/by/3.0/deed.en_US. Accessed August 28, 2013.

5. XNXX and Xvideos are two interfaces to the same corpus of videos.

6. For instance, the average runtime has been multiplied by seven. Also, runtime varies a lot between categories (23 minutes for ‘double penetration’ and four minutes for ‘men’).

7. Our dataset covers the contributions of 90,000 uploaders; one-half of them being one-time uploaders only, representing only 10% of the videos.

8. http://porngram.sexualitics.org/. Accessed August 28, 2013.

9. http://pornstudies.sexualitics.org/#catrank. Accessed August 28, 2013.

10. More precisely, denoting n(i) as the number of videos featuring tag i and n(j) as the number of videos in which j is mentioned. The edge strength is defined as the ratio between observed and theoretical values of videos using both i and j, which can be computed as s(i,j) = [n(i,j)N] / [n(i)n(j)], where N is the total number of videos.

11. The full dataset is available online: http://pornstudies.sexualitics.org/#link. Accessed August 28, 2013.

12. PornMD released an interface to explore the 10 most queried tags by country: http://www.pornmd.com/sex-seach. Pornhub, since June 2013, regularly release data and exploration tools on their data: http://www.pornhub.com/insights/. TorrentFreak looked at porn queries coming from specific countries: http://torrentfreak.com/priests-watch-dvd-screeners-while-pirates-download-filth-in-the-vatican-130407/. All sites accessed August 28, 2013.