Exploring youporn categories, tags, and nicknames for pleasant recommendations

Schuhmacher, Michael ; Zirn, Cäcilia ; Völker, Johanna

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URL: https://ub-madoc.bib.uni-mannheim.de/33272
URN: urn:nbn:de:bsz:180-madoc-332722
Document Type: Conference or workshop publication
Year of publication: 2013
Book title: Search and Exploration of X-rated Information : WSDM'13 Workshop Proceedings
The title of a journal, publication series: Sixth ACM International Conference on Web Search and Data Mining, WSDM 2013, Rome, Italy
Page range: 27-28
Date of the conference: February 5, 2013
Publisher: Murdock, Vanessa
Place of publication: New York, NY
Publishing house: ACM
ISBN: 978-90-814485-9-8
Publication language: English
Institution: School of Business Informatics and Mathematics > Praktische Informatik II (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: YouPorn is one of the largest providers of adult content on the web. Being free of charge, the video portal allows users - besides watching - to upload, categorize, and comment on pornographic videos. With this position paper, we point out the challenges of analyzing the textual data offered with the videos. We report on first experiments and problems with our YouPorn dataset , which we extracted from the non-graphical content of the YP website. To gain some insights, we performed association rule mining on the video categories and tags, and investigated preferences of users based on their nickname. Hoping that future research will be able to build upon our initial experiences, we make the ready-to-use YP dataset publicly available.

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