Deep tags: toward a quantitative analysis of online pornography

Antoine Mazieres, Mathieu Trachman, Jean-Philippe Cointet, Baptiste Coulmont, Christophe Prieur: Deep tags: toward a quantitative analysis of online pornography. In: Porn Studies, vol. 1, no. 1-2, pp. 80–95, 2014.


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.

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