Web search behavior of Internet experts and newbies
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Web searching for sexual information: an exploratory study
Information Processing and Management: an International Journal
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Youtube traffic characterization: a view from the edge
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Review: The Internet's impact on sexuality: A critical review of 15years of research
Computers in Human Behavior
Measuring serendipity: connecting people, locations and interests in a mobile 3G network
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
How useful are your comments?: analyzing and predicting youtube comments and comment ratings
Proceedings of the 19th international conference on World wide web
Strengthening forensic investigations of child pornography on P2P networks
Proceedings of the 6th International COnference
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Although according to surveys related to internet user activity it is considered one of the most popular aspects, few studies are actually concerned with internet pornography. This paper is aimed at rectifying that overlook. In particular, we study user activity related to internet pornography by looking at two main behaviors: (i) watching pornography, and (ii) providing feedback on pornography items in the form of ratings and comments. By using appropriate datasets that we collect, we make contributions related to the study of both behaviors pointed out above. With regards to viewing, we observe that views are highly dependent on pornography category and video size. By studying the feedback system of pornography video websites, we observe differences in the way users rate items across websites popular in different parts of the world. Finally, we employ sentiment analysis to study the comments that users leave on pornography websites and we find surprising similarities across the analyzed websites. Our results pave the way to understanding more about human behavior related to internet pornography and can impact, among others, fields such as content personalization, video content delivery, recommender systems