Adult content constitutes a major source of Internet traffic. As with many other platforms, these sites are incentivized to engage users and maintain them on the site. This engagement (e.g., through recommendations) shapes the journeys taken through such sites. Using data from a large content delivery network, we explore session journeys within an adult website. We take two perspectives. We first inspect the corpus available on these platforms. Following this, we investigate the session access patterns. We make a number of observations that could be exploited for optimizing delivery, e.g., that users often skip within video streams.
CITATION STYLE
Grammenos, A., Raman, A., Böttger, T., Gilani, Z., & Tyson, G. (2020). Dissecting the Workload of a Major Adult Video Portal. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12048 LNCS, pp. 267–279). Springer. https://doi.org/10.1007/978-3-030-44081-7_16
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