# Characterizing web pornography consumption from passive measurements

## TL;DR

This study analyzes passive HTTP data from 15,000 broadband users over three years to quantitatively characterize web pornography consumption, revealing user habits, trends, and facilitating future research.

## Contribution

It introduces a large anonymized dataset of passive measurements of pornography website access, enabling more accurate and privacy-preserving analysis of user behaviors.

## Key findings

- Users access pornographic websites with specific time and frequency patterns
- The dataset reveals trends and habits in pornography consumption over three years
- Public release of the dataset supports reproducibility and further research

## Abstract

Web pornography represents a large fraction of the Internet traffic, with thousands of websites and millions of users. Studying web pornography consumption allows understanding human behaviors and it is crucial for medical and psychological research. However, given the lack of public data, these works typically build on surveys, limited by different factors, e.g. unreliable answers that volunteers may (involuntarily) provide. In this work, we collect anonymized accesses to pornography websites using HTTP-level passive traces. Our dataset includes about 15 000 broadband subscribers over a period of 3 years. We use it to provide quantitative information about the interactions of users with pornographic websites, focusing on time and frequency of use, habits, and trends. We distribute our anonymized dataset to the community to ease reproducibility and allow further studies.