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2014
- handle: 10670/1.urlsvh
- hal: hal-00937745
- doi: 10.1080/23268743.2014.888214
- PRODINRA: 314120
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info:eu-repo/semantics/altIdentifier/doi/10.1080/23268743.2014.888214
info:eu-repo/semantics/OpenAccess
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Antoine Mazieres et al., « Deep Tags: Toward a Quantitative Analysis of Online Pornography », HAL-SHS : sociologie, ID : 10.1080/23268743.2014.888214
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Résumé
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 unpreced- ented 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.