Name
Abstract | ||
|---|---|---|
Pornography is massively available on the Internet, often free of charge. It represents a significant fraction of the overall Internet traffic, with thousands of websites and millions of users. Studying web pornography consumption is useful to understand human behavior, and it is crucial for different disciplines, helping in sociological, statistical and behavioral research. However, given the lack of public datasets, most of the works build on surveys, limited by multiple factors, e.g., unreliable answers that volunteers may (even unconsciously) give. In this work, we analyze anonymized accesses to pornography websites using HTTP-level traces collected from an operational network. Our dataset includes anonymized traffic from about 15000 broadband subscribers over three years. We use it to provide quantitative figures on pornographic website consumption, focusing on time and frequency of use, habits, and trends. We also compare web pornography users? interests with those who do not consume web pornography, showing notable differences. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.comnet.2021.107909 | COMPUTER NETWORKS |
Keywords | DocType | Volume |
Web pornography, Network measurements, User behavior | Journal | 189 |
ISSN | Citations | PageRank |
1389-1286 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea Morichetta | 1 | 17 | 4.54 |
| Martino Trevisan | 2 | 78 | 16.10 |
| Luca Vassio | 3 | 33 | 13.82 |
| Julia Krickl | 4 | 0 | 0.34 |