Detecting spam web pages through content analysis

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%). Categories and Subject Descriptors H.5.4 [Information Interfaces and Presentation]: Hypertext/Hypermedia; K.4.m [Computers and Society]: Miscellaneous; H.4.m [Information Systems]: Miscellaneous General Terms Measurement, Experimentation, Algorithms Keywords Web characterization, web pages, web spam, data mining

• Type: Conference
• Year: 2006
• Where: WWW
• Authors: Alexandros Ntoulas, Marc Najork, Mark Manasse, Dennis Fetterly
• Keywords: Internet Technology, Non-spam Pages, Spam Pages, Web Pages, WWW 2006