research-article

Identification of Web Spam through Clustering of Website Structures

Author:

Filippo GeraciAuthors Info & Claims

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

Pages 1447 - 1452

https://doi.org/10.1145/2740908.2742127

Published: 18 May 2015 Publication History

Abstract

Spam websites are domains whose owners are not interested in using them as gates for their activities but they are parked to be sold in the secondary market of web domains. To transform the costs of the annual registration fees in an opportunity of revenues, spam websites most often host a large amount of ads in the hope that someone who lands on the site by chance clicks on some ads. Since parking has become a widespread activity, a large number of specialized companies have come out and made parking a straightforward task that simply requires to set the domain's name servers appropriately.

Although parking is a legal activity, spam websites have a deep negative impact on the information quality of the web and can significantly deteriorate the performances of most web mining tools. For example these websites can influence search engines results or introduce an extra burden for crawling systems. In addition, spam websites represent a cost for ad bidders that are obliged to pay for impressions or clicks that have a negligible probability to produce revenues.

In this paper, we experimentally show that spam websites hosted by the same service provider tend to have similar look-and-feel. Exploiting this structural similarity we face the problem of the automatic identification of spam websites. In addition, we use the outcome of the classification for compiling the list of the name servers used by spam websites so that they can be discarded before the first connection just after the first DNS query. A dump of our dataset (including web pages and meta information) and the corresponding manual classification is freely available upon request.

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Cited By

Carpineto CRomano G(2023)Double-Constrained Consensus Clustering with Application to Online Anti-CounterfeitingApplied Sciences10.3390/app13181005013:18(10050)Online publication date: 6-Sep-2023
https://doi.org/10.3390/app131810050
M. Genovese LGeraci F(2018)Web Crawling and Processing with Limited Resources for Business Intelligence and Analytics ApplicationsJournal of Software10.17706/jsw.13.5.300-31613:5(300-316)Online publication date: May-2018
https://doi.org/10.17706/jsw.13.5.300-316
Jelodar HWang YYuan CJiang X(2017)A systematic framework to discover pattern for web spam classification2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)10.1109/IEMCON.2017.8117135(32-39)Online publication date: Oct-2017
https://doi.org/10.1109/IEMCON.2017.8117135
Show More Cited By

Index Terms

Identification of Web Spam through Clustering of Website Structures
1. Information systems
  1. Information retrieval
    1. Document representation

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cover image ACM Other conferences

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

May 2015

1602 pages

ISBN:9781450334730

DOI:10.1145/2740908

General Chairs:
Aldo Gangemi
National Research Council, Italy & Paris 13 University-CNRS, France
,
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy

Copyright © 2015 Copyright is held by the International World Wide Web Conference Committee (IW3C2).

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IW3C2: International World Wide Web Conference Committee

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 May 2015

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WWW '15

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IW3C2

WWW '15: 24th International World Wide Web Conference

May 18 - 22, 2015

Florence, Italy

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Carpineto CRomano G(2023)Double-Constrained Consensus Clustering with Application to Online Anti-CounterfeitingApplied Sciences10.3390/app13181005013:18(10050)Online publication date: 6-Sep-2023
https://doi.org/10.3390/app131810050
M. Genovese LGeraci F(2018)Web Crawling and Processing with Limited Resources for Business Intelligence and Analytics ApplicationsJournal of Software10.17706/jsw.13.5.300-31613:5(300-316)Online publication date: May-2018
https://doi.org/10.17706/jsw.13.5.300-316
Jelodar HWang YYuan CJiang X(2017)A systematic framework to discover pattern for web spam classification2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)10.1109/IEMCON.2017.8117135(32-39)Online publication date: Oct-2017
https://doi.org/10.1109/IEMCON.2017.8117135
de Savornin Lohman A(undefined)Working Document on Sustainable Justice (A full translation of a Dutch paper: 'Werkdocument Duurzame Rechtspraak')SSRN Electronic Journal10.2139/ssrn.2210027
https://doi.org/10.2139/ssrn.2210027

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