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Detecting Spam Web Pages through Content Analysis
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| Venue: | In Proceedings of international conference on World Wide Web 2006 Myle Ott, Yejin Choi, Claire Cardie |
| Citations: | 206 - 4 self |
BibTeX
@INPROCEEDINGS{Ntoulas_detectingspam,
author = {Alexandros Ntoulas and Mark Manasse},
title = {Detecting Spam Web Pages through Content Analysis},
booktitle = {In Proceedings of international conference on World Wide Web 2006 Myle Ott, Yejin Choi, Claire Cardie},
year = {}
}
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Abstract
In this paper, we continue our investigations of “web spam”: the injection of artificially-created pages into the web in order to influence the results from search engines, to drive traffic to certain pages for fun or profit. This paper considers some previously-undescribed techniques for automatically detecting spam pages, examines the effectiveness of these techniques in isolation and when aggregated using classification algorithms. When combined, our heuristics correctly identify 2,037 (86.2%) of the 2,364 spam pages (13.8%) in our judged collection of 17,168 pages, while misidentifying 526 spam and non-spam pages (3.1%).
