article

Adversarial Web Search

Authors:

Carlos Castillo,

Brian D. DavisonAuthors Info & Claims

Foundations and Trends in Information Retrieval, Volume 4, Issue 5

Pages 377 - 486

https://doi.org/10.1561/1500000021

Published: 01 May 2011 Publication History

Abstract

Web search engines have become indispensable tools for finding content. As the popularity of the Web has increased, the efforts to exploit the Web for commercial, social, or political advantage have grown, making it harder for search engines to discriminate between truthful signals of content quality and deceptive attempts to game search engines' rankings. This problem is further complicated by the open nature of the Web, which allows anyone to write and publish anything, and by the fact that search engines must analyze ever-growing numbers of Web pages. Moreover, increasing expectations of users, who over time rely on Web search for information needs related to more aspects of their lives, further deepen the need for search engines to develop effective counter-measures against deception.

In this monograph, we consider the effects of the adversarial relationship between search systems and those who wish to manipulate them, a field known as "Adversarial Information Retrieval". We show that search engine spammers create false content and misleading links to lure unsuspecting visitors to pages filled with advertisements or malware. We also examine work over the past decade or so that aims to discover such spamming activities to get spam pages removed or their effect on the quality of the results reduced.

Research in Adversarial Information Retrieval has been evolving over time, and currently continues both in traditional areas (e.g., link spam) and newer areas, such as click fraud and spam in social media, demonstrating that this conflict is far from over.

References

[1]

B. A, K. Csalogány, and T. Sarlós, "Link-based similarity search to fight Web spam," in Proceedings of the Second International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), 2006.

[2]

J. Abernethy and O. Chapelle, "Semi-supervised classification with hyperlinks," in Proceedings of the ECML/PKDD Graph Labeling Workshop, September 2007.

[3]

J. Abernethy, O. Chapelle, and C. Castillo, "Webspam identification through content and hyperlinks," in Proceedings of the Fourth International Workshop on Adversarial Information Retrieval on the Web (AIRWEB), pp. 41-44, ICPS: ACM Press, April 2008.

[4]

J. Abernethy, O. Chapelle, and C. Castillo, "Graph regularization methods for web spam detection," Machine Learning Journal, vol. 81, no. 2, pp. 207-225, 2010.

Digital Library

[5]

S. Adali, T. Liu, and M. Magdon-Ismail, "Optimal link bombs are uncoordinated," in Proceedings of the First International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), May 2005.

[6]

B. T. Adler and L. de Alfaro, "A content-driven reputation system for the Wikipedia," in Proceedings of the 16th International Conference on World Wide Web (WWW), pp. 261-270, New York, NY, USA: ACM, 2007.

[7]

E. Amitay, S. Yogev, and E. Yom-Tov, "Serial sharers: Detecting split identities of Web authors," in Workshop on Plagiarism Analysis, Authorship Identification, And Near-Duplicate Detection, July 2007.

[8]

R. Andersen, C. Borgs, J. Chayes, J. Hopcraft, V. Mirrokni, and S.-H. Teng, "Local computation of PageRank contributions," in Algorithms and Models for the Web-Graph, vol. 4863 of Lecture Notes in Computer Science, pp. 150- 165, Springer, 2007.

[9]

A. Arasu, J. Cho, H. Garcia-Molina, A. Paepcke, and S. Raghavan, "Searching the Web," ACM Transactions on the Internet Technology (TOIT) 1, vol. 1, pp. 2-43, August 2001.

Digital Library

[10]

J. Attenberg and T. Suel, "Cleaning search results using term distance features," in Proceedings of the Fourth International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 21-24, New York, NY, USA: ACM, 2008.

[11]

V. Bacarella, F. Giannotti, M. Nanni, and D. Pedreschi, "Discovery of ads Web hosts through traffic data analysis," in Proceedings of the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD), pp. 76-81, New York, NY, USA: ACM, 2004.

[12]

R. Baeza-Yates, C. Castillo, and V. López, "PageRank increase under different collusion topologies," in First International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 17-24, May 2005.

[13]

R. Baeza-Yates and B. Ribeiro-Neto, "Modern Information Retrieval," Addison Wesley, May 1999.

[14]

J. Bar-Ilan, "Web links and search engine ranking: The case of Google and the query "jew"," Journal of the American Society for Information Science and Technology, vol. 57, no. 12, pp. 1581-1589, 2006.

Digital Library

[15]

J. Bar-Ilan, "Google bombing from a time perspective," Journal of Computer-Mediated Communication, vol. 12, no. 3, 2007.

[16]

Z. Bar-Yossef, I. Keidar, and U. Schonfeld, "Do not crawl in the DUST: Different URLs with similar text," ACM Transactions on the Web, vol. 3, no. 1, pp. 1-31, 2009.

Digital Library

[17]

J. Battelle, The Search: How Google and Its Rivals Rewrote the Rules of Business and Transformed Our Culture. New York: Portfolio, 2005.

[18]

L. Becchetti, C. Castillo, D. Donato, R. Baeza-Yates, and S. Leonardi, "Link analysis for Web spam detection," ACM Transactions on the Web, vol. 2, no. 1, pp. 1-42, February 2008.

Digital Library

[19]

L. Becchetti, C. Castillo, D. Donato, S. Leonardi, and R. Baeza-Yates, "Using rank propagation and probabilistic counting for link-based spam detection," in Proceedings of the Workshop on Web Mining and Web Usage Analysis (WebKDD), ACM Press, August 2006.

[20]

A. A. Benczúr, I. Bíró, K. Csalogány, and M. Uher, "Detecting nepotistic links by language model disagreement," in Proceedings of the 15th International Conference on World Wide Web (WWW), pp. 939-940, ACM Press, 2006.

[21]

A. A. Benczúr, K. Csalogány, T. Sarlós, and M. Uher, "SpamRank: Fully automatic link spam detection," in Proceedings of the First International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), May 2005.

[22]

F. Benevenuto, T. Rodrigues, V. Almeida, J. Almeida, C. Zhang, and K. Ross, "Identifying video spammers in online social networks," in Proceedings of the Fourth International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 45-52, New York, NY, USA: ACM, 2008.

[23]

P. Berkhin, "A survey on PageRank computing," Internet Mathematics, vol. 2, no. 2, pp. 73-120, 2005.

[24]

K. Berlt, E. S. de Moura, C. M. André, N. Ziviani, and T. Couto, "A hypergraph model for computing page reputation on Web collections," in Proceedings of the Simpósio Brasileiro de Banco de Dados (SBBD), pp. 35-49, October 2007.

[25]

K. Bharat and M. R. Henzinger, "Improved algorithms for topic distillation in hyperlinked environments," in Proceedings of the 21st International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 104-111, August 1998.

[26]

J. Bian, Y. Liu, E. Agichtein, and H. Zha, "A few bad votes too many?: Towards robust ranking in social media," in Proceedings of the Fourth International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 53-60, New York, NY, USA: ACM, 2008.

[27]

A. Bifet, C. Castillo, P.-A. Chirita, and I. Weber, "An analysis of factors used in search engine ranking," in Proceedings of the First International Workshop on Adversarial Information Retrieval (AIRWeb), May 2005.

[28]

I. Bíró, D. Siklósi, J. Szabó, and A. Benczúr, "Linked latent dirichlet allocation in Web spam filtering," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 37-40, ACM Press, 2009.

[29]

I. Bíró, J. Szabó, and A. A. Benczúr, "Latent dirichlet allocation in Web spam filtering," in Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 29-32, New York, NY, USA: ACM, 2008.

[30]

D. M. Blei, A. Y. Ng, and M. I. Jordan, "Latent dirichlet allocation," Journal of Machine Learning Research, vol. 3, pp. 993-1022, 2003.

Digital Library

[31]

A. Borodin, G. O. Roberts, J. S. Rosenthal, and P. Tsaparas, "Finding authorities and hubs from link structures on the World Wide Web," in Proceedings of the 10th International Conference on World Wide Web (WWW), pp. 415-429, 2001.

[32]

O. P. Boykin and V. Roychowdhury, "Personal Email networks: an effective anti-spam tool," Condensed Matter cond-mat/0402143, 2004.

[33]

S. Brin, R. Motwani, L. Page, and T. Winograd, "What can you do with a Web in your pocket?," Data Engineering Bulletin, vol. 21, no. 2, pp. 37-47, 1998.

[34]

S. Brin and L. Page, "The anatomy of a large-scale hypertextual Web search engine," in Proceedings of the 7th International Conference on the World Wide Web, pp. 107-117, April 1998.

[35]

A. Brod and R. Shivakumar, "Advantageous semi-collusion," The Journal of Industrial Economics, vol. 47, no. 2, pp. 221-230, 1999.

[36]

A. Z. Broder, S. C. Glassman, M. S. Manasse, and G. Zweig, "Syntactic clustering of the Web," Computer Networks and ISDN Systems, vol. 29, no. 8-13, pp. 1157-1166, September 1997.

Digital Library

[37]

T. A. Brooks, "Web search: How the Web has changed information retrieval," Information Research, vol. 8, no. 3, April 2003.

[38]

G. Buehrer, J. W. Stokes, and K. Chellapilla, "A large-scale study of automated Web search traffic," in Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 1-8, New York, NY, USA: ACM, 2008.

[39]

S. Büttcher, C. L. A. Clarke, and B. Lushman, "Term proximity scoring for ad-hoc retrieval on very large text collections," in Proceedings of the 29th ACM Annual SIGIR Conference on Research and Development in Information Retrieval, pp. 621-622, New York, NY, USA: ACM Press, 2006.

[40]

C. Castillo, "Effective Web Crawling," PhD thesis, University of Chile, 2004.

[41]

C. Castillo, C. Corsi, D. Donato, P. Ferragina, and A. Gionis, "Query log mining for detecting polysemy and spam," in Proceedings of the KDD Workshop on Web Mining and Web Usage Analysis (WEBKDD), Springer: LNCS, August 2008.

[42]

C. Castillo, C. Corsi, D. Donato, P. Ferragina, and A. Gionis, "Query-log mining for detecting spam," in Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), ICPS: ACM Press, April 2008.

[43]

C. Castillo, D. Donato, L. Becchetti, P. Boldi, S. Leonardi, M. Santini, and S. Vigna, "A reference collection for Web spam," SIGIR Forum, vol. 40, no. 2, pp. 11-24, December 2006.

Digital Library

[44]

C. Castillo, D. Donato, A. Gionis, V. Murdock, and F. Silvestri, "Know your neighbors: Web spam detection using the web topology," in Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, July 2007.

[45]

J. Caverlee, "Tamper-Resilient Methods for Web-Based Open Systems," PhD thesis, College of Computing, Georgia Institute of Technology, August 2007.

[46]

J. Caverlee and L. Liu, "Countering Web spam with credibility-based link analysis," in Proceedings of the Twenty-Sixth Annual ACM Symposium on Principles of Distributed Computing (PODC), pp. 157-166, New York, NY, USA: ACM, 2007.

[47]

J. Caverlee, L. Liu, and S. Webb, "Socialtrust: Tamper-resilient trust establishment in online communities," in Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL), pp. 104-114, 2008.

[48]

J. Caverlee, L. Liu, and S. Webb, "Towards robust trust establishment in Web-based social networks with SocialTrust," in Proceedings of the 17th International World Wide Web Conference (WWW), pp. 1163-1164, ACM, 2008.

[49]

J. Caverlee, S. Webb, and L. Liu, "Spam-resilient Web rankings via influence throttling," in Proceedings of the IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 1-10, 2007.

[50]

K. Chellapilla and D. M. Chickering, "Improving cloaking detection using search query popularity and monetizability," in Proceedings of the 2nd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 17-24, August 2006.

[51]

K. Chellapilla and A. Maykov, "A taxonomy of JavaScript redirection spam," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 81-88, New York, NY, USA: ACM Press, 2007.

[52]

A. Cheng and E. Friedman, "Manipulability of PageRank under sybil strategies," in Proceedings of the First Workshop on the Economics of Networked Systems (NetEcon06), 2006.

[53]

Y.-J. Chung, M. Toyoda, and M. Kitsuregawa, "A study of link farm distribution and evolution using a time series of Web snapshots," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 9-16, ACM Press, 2009.

[54]

A. Clausen, "The cost of attack of PageRank," in Proceedings of the International Conference on Agents, Web Technologies and Internet Commerce (IAWTIC), July 2004.

[55]

G. V. Cormack, "Email spam filtering: A systematic review," Foundations and Trends in Information Retrieval 1, pp. 335-455, 2008.

Digital Library

[56]

G. V. Cormack, M. Smucker, and C. L. Clarke, "Efficient and effective spam filtering and re-ranking for large web datasets," Unpublished draft, available from http://durum0.uwaterloo.ca/clueweb09spam/spamhunt.pdf, retrieved 10, April 2010.

[57]

N. Craswell, O. Zoeter, M. Taylor, and B. Ramsey, "An experimental comparison of click position-bias models," in Proceedings of the First International Conference on Web Search and Data Mining (WSDM), pp. 87-94, New York, NY, USA: ACM, 2008.

[58]

B. Croft, D. Metzler, and T. Strohman, Search Engines: Information Retrieval in Practice. Addison Wesley, 2009.

Digital Library

[59]

A. L. C. da Costa-Carvalho, P.-A. Chirita, E. S. de Moura, P. Calado, and W. Nejdl, "Site level noise removal for search engines," in Proceedings of the 15th International Conference on World Wide Web (WWW), pp. 73-82, New York, NY, USA: ACM Press, 2006.

[60]

N. Dai, B. Davison, and X. Qi, "Looking into the past to better classify Web spam," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 1-8, ACM Press, 2009.

[61]

N. Daswani and M. Stoppelman, "The anatomy of Clickbot. A," in Proceedings of the USENIX HOTBOTS Workshop, April 2007.

[62]

B. D. Davison, "Recognizing nepotistic links on the Web," in Artificial Intelligence for Web Search, pp. 23-28, AAAI Press, July 2000.

[63]

B. D. Davison, M. Najork, and T. Converse, "Adversarial information retrieval on the Web (AIRWeb 2006)," SIGIR Forum, vol. 40, no. 2, pp. 27-30, 2006.

Digital Library

[64]

J. Douceur, "The sybil attack," in Proceedings of the First International Peer To Peer Systems Workshop (IPTPS), pp. 251-260, Springer: Vol. 2429 of Lecture Notes in Computer Science, January 2002.

[65]

I. Drost and T. Scheffer, "Thwarting the nigritude ultramarine: Learning to identify link spam," in Proceedings of the 16th European Conference on Machine Learning (ECML), pp. 233-243, Vol. 3720 of Lecture Notes in Artificial Intelligence, 2005.

[66]

Y. Du, Y. Shi, and X. Zhao, "Using spam farm to boost PageRank," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 29-36, New York, NY, USA: ACM, 2007.

[67]

O. Duskin and D. G. Feitelson, "Distinguishing humans from robots in Web search logs: Preliminary results using query rates and intervals," in Proceedings of the WSDM Workshop on Web Search Click Data (WSCD), pp. 15-19, New York, NY, USA: ACM, 2009.

[68]

M. Egele, C. Kruegel, and E. Kirda, "Removing web spam links from search engine results," Journal in Computer Virology, In press. Published online 22 August, 2009.

[69]

N. Eiron, K. S. Curley, and J. A. Tomlin, "Ranking the Web frontier," in Proceedings of the 13th International Conference on World Wide Web, pp. 309- 318, New York, NY, USA: ACM Press, 2004.

[70]

E. Enge, "Matt cutts interviewed by eric enge," Article online at http://www. stonetemple.com/articles/interview-matt-cutts-012510.shtml and retrieved on 11 April 2010, March 2010.

[71]

M. Erdélyi, A. A. Benczúr, J. Masanes, and D. Siklósi, "Web spam filtering in internet archives," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 17-20, ACM Press, 2009.

[72]

J. Feigenbaum, S. Kannan, M. A. McGregor, S. Suri, and J. Zhang, "On graph problems in a semi-streaming model," in Proceedings of the 31st International Colloquium on Automata, Languages and Programming (ICALP), pp. 531- 543, Springer: Vol. 3142 of LNCS, 2004.

[73]

D. Fetterly, "Adversarial Information Retrieval: the manipulation of Web content," ACM Computing Reviews, July 2007.

[74]

D. Fetterly, M. Manasse, and M. Najork, "Spam, damn spam, and statistics: Using statistical analysis to locate spam Web pages," in Proceedings of the Seventh Workshop on the Web and databases (WebDB), pp. 1-6, June 2004.

[75]

D. Fetterly, M. Manasse, and M. Najork, "Detecting phrase-level duplication on the World Wide Web," in Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 170-177, New York, NY, USA: ACM, 2005.

[76]

R. Fishkin, "Lessons learned building an index of the WWW," Retrieved 15 June 2009 from http://www.seomoz.org/blog/lessons-learned-building-anindex-of-the-www, April 2009.

[77]

S. Fox, M. Madden, and A. Smith, "Digital footprints," Pew Internet and American Life report. Retrieved 15 June 2009 from http://www.pewinternet. org/Reports/2007/Digital-Footprints.aspx, December 2007.

[78]

Q. Gan and T. Suel, "Improving Web spam classifiers using link structure," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 17-20, New York, NY, USA: ACM, 2007.

[79]

D. Gibson, R. Kumar, and A. Tomkins, "Discovering large dense subgraphs in massive graphs," in Proceedings of the 31st International Conference on Very Large Data Bases (VLDB), pp. 721-732, VLDB Endowment, 2005.

[80]

Y. Gil and D. Artz, "Towards content trust of Web resources," in Proceedings of the 15th International Conference on World Wide Web (WWW), pp. 565- 574, New York, NY, USA: ACM, 2006.

[81]

A. Gkanogiannis and T. Kalamboukis, "An algorithm for text categorization," in Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 869-870, New York, NY, USA: ACM, 2008.

[82]

A. Gkanogiannis and T. Kalamboukis, "A novel supervised learning algorithm and its use for spam detection in social bookmarking systems," in Proceedings of the ECML/PKDD Discovery Challenge, 2008.

[83]

H. L. Gomes, B. R. Almeida, A. M. L. Bettencourt, V. Almeida, and M. J. Almeida, "Comparative graph theoretical characterization of networks of spam and legitimate email," April 2005.

[84]

M. Goodstein and V. Vassilevska, "A two player game to combat WebSpam," Technical Report, Carnegie Mellon University, 2007.

[85]

M. Gori and I. Witten, "The bubble of Web visibility," Communications of the ACM, vol. 48, no. 3, pp. 115-117, March 2005.

Digital Library

[86]

P. Gramme and J.-F. Chevalier, "Rank for spam detection -- ECML discovery challenge," in Proceedings of the ECML/PKDD Discovery Challenge, 2008.

[87]

A. L. Granka, T. Joachims, and G. Gay, "Eye-tracking analysis of user behavior in www search," in Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 478-479, New York, NY, USA: ACM, 2004.

[88]

J. Grappone and G. Couzin, Search Engine Optimization: An Hour a Day. Wiley, 2006.

[89]

R. Guha, R. Kumar, P. Raghavan, and A. Tomkins, "Propagation of trust and distrust," in Proceedings of the 13th International Conference on World Wide Web (WWW), pp. 403-412, New York, NY, USA: ACM Press, 2004.

[90]

D. M. Guinness, H. Zeng, Li, D. Narayanan, and M. Bhaowal, "Investigations into trust for collaborative information. repositories: A Wikipedia case study," in Proceedings of workshop on Models of Trust for the Web (MTW06), May 2006.

[91]

Z. Gyöngyi and H. Garcia-Molina, "Link spam alliances," in Proceedings of the 31st International Conference on Very Large Data Bases (VLDB), pp. 517- 528, 2005.

[92]

Z. Gyöngyi and H. Garcia-Molina, "Spam: It's not just for inboxes anymore," IEEE Computer Magazine, vol. 38, no. 10, pp. 28-34, 2005.

Digital Library

[93]

Z. Gyöngyi and H. Garcia-Molina, "Web spam taxonomy," in Proceedings of the First International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 39-47, May 2005.

[94]

Z. Gyöngyi, H. Garcia-Molina, and J. Pedersen, "Combating Web spam with TrustRank," in Proceedings of the 30th International Conference on Very Large Data Bases (VLDB), pp. 576-587, Morgan Kaufmann, August 2004.

[95]

Z. I. Gyöngyi, "Applications of Web link analysis," PhD thesis, Stanford University, Adviser: Hector Garcia-Molina, 2008.

[96]

Z. P. Gyöngyi, P. Berkhin, H. Garcia-Molina, and J. Pedersen, "Link spam detection based on mass estimation," in Proceedings of the 32nd International Conference on Very Large Databases (VLDB), pp. 439-450, 2006.

[97]

H. T. Haveliwala, "Topic-sensitive PageRank," in Proceedings of the Eleventh World Wide Web Conference (WWW), pp. 517-526, ACM Press, May 2002.

Digital Library

[98]

R. M. Henzinger, R. Motwani, and C. Silverstein, "Challenges in Web search engines," SIGIR Forum, vol. 37, no. 2, 2002.

[99]

R. Herbrich, T. Graepel, and K. Obermayer, "Large margin rank boundaries for ordinal regression," in Advances in Large Margin Classifiers, (Smola, Bartlett, Schoelkopf, and Schuurmans, eds.), pp. 115-132, Cambridge, MA: MIT Press, 2000.

[100]

A. Heydon and M. Najork, "Mercator: A scalable, extensible web crawler," World Wide Web, vol. 2, no. 4, pp. 219-229, 1999.

Digital Library

[101]

P. Heymann, G. Koutrika, and H. Garcia-Molina, "Fighting spam on social Web sites: A survey of approaches and future challenges," IEEE Internet Computing, vol. 11, no. 6, pp. 36-45, 2007.

Digital Library

[102]

J. Hopcroft and D. Sheldon, "Manipulation-resistant reputations using hitting time," in Proceedings of the Workshop on Algorithms and Models for the Web-Graph (WAW), pp. 68-81, Springer: Vol. 2863 of Lecture Notes in Computer Science, December 2007. Also appears in Internet Mathematics 5, 5:71-90, 2009.

[103]

J. Hopcroft and D. Sheldon, "Network reputation games," Techical Report, Cornell University, October 2008.

[104]

M. Hu, E.-P. Lim, A. Sun, W. H. Lauw, and B.-Q. Vuong, "Measuring article quality in Wikipedia: Models and evaluation," in Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management (CIKM), pp. 243-252, New York, NY, USA: ACM, 2007.

[105]

S. Hutcheon, "Google pardons BMW website," in Sydney Morning Herald, Retrieved 18 June 2009 from http://www.smh.com.au/news/breaking/googlepardons-bmw-website/2006/02/09/1139379597733.html, February 2006.

[106]

N. Immorlica, K. Jain, and M. Mahdian, "Game-theoretic aspects of designing hyperlink structures," in Proceedings of the 2nd Workshop on Internet and Network Economics (WINE), pp. 150-161, Vol. 4286, Springer LNCS, December 2006.

[107]

N. Immorlica, K. Jain, M. Mahdian, and K. Talwar, "Click fraud resistant methods for learning click-through rates," in Proceedings of the Workshop on Internet and Network Economics (WINE), pp. 34-45, Springer, Berlin: Vol. 3828 of Lecture Notes in Computer Science, 2005.

[108]

M. Jamali and M. Ester, "Trustwalker: A random walk model for combining trust-based and item-based recommendation," in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 397-406, New York, NY, USA: ACM, 2009.

[109]

J. B. Jansen, "Click fraud," Computer, vol. 40, no. 7, pp. 85-86, 2007.

Digital Library

[110]

Q. Jiang, L. Zhang, Y. Zhu, and Y. Zhang, "Larger is better: Seed selection in link-based anti-spamming algorithms," in Proceedings of the 17th International Conference on World Wide Web (WWW), pp. 1065-1066, New York, NY, USA: ACM, 2008.

[111]

N. Jindal and B. Liu, "Analyzing and detecting review spam," in Proceedings of the 7th IEEE International Conference on Data Mining (ICDM), pp. 547- 552, 2007.

[112]

N. Jindal and B. Liu, "Review spam detection," in Proceedings of the 16th International Conference on World Wide Web (WWW), pp. 1189-1190, New York, NY, USA: ACM Press, 2007.

[113]

N. Jindal and B. Liu, "Opinion spam and analysis," in Proceedings of the International Conference on Web Search and Data Mining (WSDM), pp. 219- 230, New York, NY, USA: ACM, 2008.

[114]

T. Joachims, "Optimizing search engines using clickthrough data," in Proceedings of the ACM Conference on Knowledge Discovery and Data Mining (KDD), pp. 133-142, New York, NY: ACM Press, 2002.

[115]

T. Joachims, L. Granka, B. Pan, H. Hembrooke, and G. Gay, "Accurately interpreting clickthrough data as implicit feedback," in Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 154-161, New York, NY, USA: ACM Press, 2005.

[116]

T. Jones, D. Hawking, and R. Sankaranarayana, "A framework for measuring the impact of Web spam," in Proceedings of 12th Australasian Document Computing Symposium (ADCS), December 2007.

[117]

T. Jones, D. Hawking, R. Sankaranarayana, and N. Craswell, "Nullification test collections for Web spam and SEO," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 53-60, New York, NY, USA: ACM, April 2009.

[118]

T. Z. Jr., "Gaming the search engine, in a political season," in New York Times, November 2006.

[119]

D. S. Kamvar, T. M. Schlosser, and H. Garcia-Molina, "The Eigentrust algorithm for reputation management in P2P networks," in Proceedings of the 12th International Conference on World Wide Web (WWW), pp. 640-651, New York, NY, USA: ACM Press, 2003.

[120]

G. Karypis and V. Kumar, "Multilevel k-way partitioning scheme for irregular graphs," Journal of Parallel and Distributed Computation, vol. 48, no. 1, pp. 96-129, 1998.

Digital Library

[121]

T. Katayama, T. Utsuro, Y. Sato, T. Yoshinaka, Y. Kawada, and T. Fukuhara, "An empirical study on selective sampling in active learning for Splog detection," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 29-36, ACM Press, 2009.

[122]

M. J. Kleinberg, "Authoritative sources in a hyperlinked environment," Journal of the ACM, vol. 46, no. 5, pp. 604-632, 1999.

Digital Library

[123]

J. Köhne, "Optimizing a large dynamically generated Website for search engine crawling and ranking," Master's thesis, Technical University of Delft, 2006.

[124]

P. Kolari, "Detecting Spam Blogs: An Adaptive Online Approach," PhD thesis, Department of Computer Science and Electrical Engineering, University of Maryland-Baltimore County, 2007.

[125]

P. Kolari, T. Finin, A. Java, and A. Joshi, "Splog blog dataset," Techical Report, UMBC ebiquity, 2006.

[126]

P. Kolari, T. Finin, A. Java, and A. Joshi, "Towards spam detection at ping servers," in Proceedings of the International Conference on Weblogs and Social Media (ICWSM), AAAI Press. Demo, March 2007.

[127]

P. Kolari, A. Java, and T. Finin, "Characterizing the Splogosphere," in Proceedings of the 3rd Annual Workshop on the Weblogging Ecosystem, 2006.

[128]

P. Kolari, A. Java, T. Finin, T. Oates, and A. Joshi, "Detecting spam blogs: A machine learning approach," in Proceedings of the National Conference on Artificial Intelligence (AAAI), July 2006.

[129]

A. Korolova, K. Kenthapadi, N. Mishra, and A. Ntoulas, "Releasing search queries and clicks privately," in Proceedings of the 18th International Conference on World Wide Web (WWW), pp. 171-180, New York, NY, USA: ACM, 2009.

[130]

M. Koster, "A standard for robot exclusion," http://www.robotstxt.org/wc/ robots.html, 1996.

[131]

Z. Kou, "Stacked graphical learning," PhD thesis, School of Computer Science, Carnegie Mellon University, 2007.

[132]

G. Koutrika, A. F. Effendi, Z. Gyöngyi, P. Heymann, and H. Garcia-Molina, "Combating spam in tagging systems," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 57-64, New York, NY, USA: ACM Press, 2007.

[133]

G. Koutrika, A. F. Effendi, Z. Gyöngyi, P. Heymann, and H. Garcia-Molina, "Combating spam in tagging systems: An evaluation," ACM Transactions on the Web, vol. 2, no. 4, pp. 1-34, 2008.

Digital Library

[134]

B. Krause, H. A. Schimitz, and G. Stumme, "The anti-social tagger -- detecting spam in social bookmarking systems," in Proceedings of the Fourth International Workshop on Adversarial Information Retrieval on the Web (AIRWeb) , April 2008.

[135]

V. Krishnan and R. Raj, "Web spam detection with anti-TrustRank," in Proceedings of the 2nd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 37-40, 2006.

[136]

R. Kumar, J. Novak, B. Pang, and A. Tomkins, "On anonymizing query logs via token-based hashing," in Proceedings of the 16th International Conference on World Wide Web (WWW), pp. 629-638, New York, NY, USA: ACM Press, 2007.

[137]

J. Kupke and M. Ohye, "Specify your canonical," Retrieved 18 June 2009 from http://googlewebmastercentral.blogspot.com/2009/02/specify-your-canonical.html, February 2009.

[138]

N. A. Langville and D. C. Meyer, "Deeper inside PageRank," Internet Mathematics, vol. 1, no. 3, pp. 335-380, 2003.

[139]

N. A. Langville and D. C. Meyer, Google's PageRank and Beyond: The Science of Search Engine Rankings. Princeton, NJ: Princeton University Press, 2006.

Digital Library

[140]

H.-T. Lee, D. Leonard, X. Wang, and D. Loguinov, "Irlbot: Scaling to 6 billion pages and beyond," ACM Transactions on the Web, vol. 3, no. 3, pp. 1-34, 2009.

Digital Library

[141]

R. Lempel and S. Moran, "The stochastic approach for link-structure analysis (SALSA) and the TKC effect," Computer Networks, vol. 33, no. 1-6, pp. 387- 401, 2000.

Digital Library

[142]

R. Levien and A. Aiken, "Attack-resistant trust metrics for public key certification," in Proceedings of the 7th USENIX Security Symposium, pp. 229-242, 1998.

[143]

J. Lewis, "Google bombs," in LA Weekly, Retrieved June 1, 2009 from http://www.laweekly.com/2003-12-25/news/google-bombs, December 2003.

[144]

G. Liang, "Surveying Internet usage and impact in five Chinese cities," Report of the Research Center for Social Development, Chinese Academy of Social Sciences. Retrieved 15 June 2009 from http://news.bbc.co.uk/1/shared/bsp/hi/ pdfs/10_02_06_china.pdf, November 2005.

[145]

M. Lifantsev, "Voting model for ranking Web pages," in Proceedings of the International Conference on Internet Computing (IC), (P. Graham and M. Maheswaran, eds.), pp. 143-148, CSREA Press, June 2000.

[146]

J.-L. Lin, "Detection of cloaked Web spam by using tag-based methods," Expert Systems with Applications, vol. 36, no. 4, pp. 7493-7499, May 2009.

Digital Library

[147]

Y.-R. Lin, H. Sundaram, Y. Chi, J. Tatemura, and L. B. Tseng, "Splog detection using self-similarity analysis on blog temporal dynamics," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 1-8, New York, NY, USA: ACM Press, 2007.

[148]

Y.-R. Lin, H. Sundaram, Y. Chi, J. Tatemura, and L. B. Tseng, "Detecting splogs via temporal dynamics using self-similarity analysis," ACM Transations on the Web, vol. 2, no. 1, pp. 1-35, 2008.

Digital Library

[149]

T. Liu, "Analyzing the importance of group structure in the Google Page-Rank algorithm," Master's thesis, Rensselaer Polytechnic Institute, November 2004.

[150]

Y. Liu, R. Cen, M. Zhang, S. Ma, and L. Ru, "Identifying Web spam with user behavior analysis," in Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 9-16, New York, NY, USA: ACM, 2008.

[151]

Y. Liu, B. Gao, T.-Y. Liu, Y. Zhang, Z. Ma, S. He, and H. Li, "Browse-Rank: Letting web users vote for page importance," in Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 451-458, New York, NY, USA: ACM, 2008.

[152]

J. Ma, K. L. Saul, S. Savage, and M. G. Voelker, "Beyond blacklists: Learning to detect malicious web sites from suspicious urls," in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1245-1254, New York, NY, USA: ACM, 2009.

[153]

C. C. Mann, "How click fraud could swallow the internet," Wired, vol. 14, no. 1, January 2006.

[154]

D. C. Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval. Cambridge University Press, 2008.

Digital Library

[155]

B. Markines, C. Cattuto, and F. Menczer, "Social spam detection," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 41-48, New York, NY, USA: ACM, 2009.

[156]

K. Marks and T. Celik, "Microformats: The rel=nofollow attribute," Techical Report, Technorati, 2005. Online at http://microformats.org/wiki/relnofollow. Last accessed 29 January 2009.

[157]

K. Marks and T. Celik, "Microformats: Vote links," Technical Report, Technorati, 2005. Online at http://microformats.org/wiki/vote-links. Last accessed 29 January 2009.

[158]

S. Marti and H. Garcia-Molina, "Taxonomy of trust: Categorizing P2P reputation systems," Computer Networks, vol. 50, no. 4, pp. 472-484, March 2006.

Digital Library

[159]

J. Martinez-Romo and L. Araujo, "Web spam identification through language model analysis," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 21-28, ACM Press, 2009.

[160]

K. Mason, "Detecting Colluders in PageRank: Finding Slow Mixing States in a Markov Chain," PhD thesis, Department of Engineering Economic Systems and Operations Research, Stanford University, September 2005.

[161]

P. Massa and C. Hayes, "Page-reRank: Using trusted links to re-rank authority," in Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI), pp. 614-617, 2005.

[162]

A. Mathes, "Filler Friday: Google Bombing," Retrieved June 1, 2009 from http://uber.nu/2001/04/06/, April 2001.

[163]

T. McNichol, "Engineering Google results to make a point," New York Times, January 2004.

[164]

T. P. Metaxas and J. Destefano, "Web spam, propaganda and trust," in Proceedings of the First International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), May 2005.

[165]

A. Metwally, D. Agrawal, and E. A. Abbadi, "Detectives: Detecting coalition hit inflation attacks in advertising networks streams," in Proceedings of the 16th International Conference on World Wide Web (WWW), pp. 241-250, New York, NY, USA: ACM Press, 2007.

[166]

A. G. Mishne, "Applied Text Analytics for Blogs," PhD thesis, University of Amsterdam, April 2007.

[167]

G. Mishne, D. Carmel, and R. Lempel, "Blocking blog spam with language model disagreement," in Proceedings of the 1st International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), May 2005.

[168]

T. Moore and R. Clayton, "Evil searching: Compromise and recompromise of internet hosts for phishing," in Financial Cryptography and Data Security, pp. 256-272, Springer, 2009.

[169]

M. Moran and B. Hunt, Search Engine Marketing, Inc. Upper Saddle River, NJ: IBM Press, 2006.

[170]

A. Moshchuk, T. Bragin, D. S. Gribble, and M. H. Levy, "A crawler-based study of spyware on the web," in Proceedings of the Network and Distributed System Security Symposium (NDSS), pp. 17-33, February 2006.

[171]

R. Moulton and K. Carattini, "A quick word about Googlebombs," Retrieved June 1, 2009 from http://googlewebmastercentral.blogspot.com/ 2007/01/quick-word-about-googlebombs.html, January 2007.

[172]

L. Mui, M. Mohtashemi, and A. Halberstadt, "A computational model of trust and reputation," in Proceedings of the 35th Hawaii International Conference on System Science (HICSS), 2002.

[173]

M. Najork, "System and method for identifying cloaked web servers," U.S. Patent 6,910,077 (issued June 2005), 2002.

[174]

N. Neubauer, R. Wetzker, and K. Obermayer, "Tag spam creates large nongiant connected components," in Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 49-52, ACM Press, 2009.

[175]

B. News, "Miserable failure' links to Bush: George W Bush has been Google bombed," http://news.bbc.co.uk/2/hi/americas/3298443.stm, December 2003.

[176]

L. Nie, D. B. Davison, and B. Wu, "Incorporating trust into Web authority," Technical Report LU-CSE-07-002, Department of Computer Science and Engineering, Lehigh University, 2007.

[177]

L. Nie, B. Wu, and D. B. Davison, "A cautious surfer for PageRank," in Proceedings of the 16th International Conference on World Wide Web (WWW), pp. 1119-1120, New York, NY, USA: ACM Press, 2007.

[178]

L. Nie, B. Wu, and D. B. Davison, "Winnowing wheat from the chaff: Propagating trust to sift spam from the Web," in Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 869-870, July 2007.

[179]

Y. Niu, Y.-M. Wang, H. Chen, M. Ma, and F. Hsu, "A quantitative study of forum spamming using context-based analysis," in Proceedings of the 14th Annual Network and Distributed System Security Symposium (NDSS), pp. 79- 92, February 2007.

[180]

A. Ntoulas, "Crawling and searching the HiddenWeb," PhD thesis, University of California at Los Angeles, Los Angeles, CA, USA, 2006. Adviser-Cho, Junghoo.

[181]

A. Ntoulas, J. Cho, and C. Olston, "What's new on the Web?: The evolution of the Web from a search engine perspective," in Proceedings of the 13th International Conference on World Wide Web, pp. 1-12, New York, NY, USA: ACM Press, 2004.

[182]

A. Ntoulas, M. Najork, M. Manasse, and D. Fetterly, "Detecting spam Web pages through content analysis," in Proceedings of the 15th International Conference on World Wide Web (WWW), pp. 83-92, May 2006.

[183]

L. Page, S. Brin, R. Motwani, and T. Winograd, "The PageRank citation ranking: Bringing order to the Web," Techincal Report, Stanford University, 1998. Available from http://dbpubs.stanford.edu/pub/1999-66.

[184]

R. C. Palmer, B. P. Gibbons, and C. Faloutsos, "ANF: A fast and scalable tool for data mining in massive graphs," in Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 81-90, New York, NY, USA: ACM Press, 2002.

[185]

K. Park, V. S. Pai, K.-W. Lee, and S. Calo, "Securing Web service by automatic robot detection," in Proceedings of the USENIX Annual Technical Conference, pp. 255-260, 2006.

[186]

J.-X. Parreira, D. Donato, C. Castillo, and G. Weikum, "Computing trusted authority scores in peer-to-peer networks," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 73-80, ACM Press, May 2007.

[187]

L. A. Penenberg, "Click fraud threatens Web," Wired, October 2004.

[188]

L. A. Penenberg, "Legal showdown in search fracas," in Wired, Retrieved 18 June 2009 from http://www.wired.com/culture/lifestyle/news/2005/ 09/68799, September 2005.

[189]

A. Perkins, "The classification of search engine spam," Available online at http://www.silverdisc.co.uk/articles/spam-classification/, September 2001.

[190]

J. Piskorski, M. Sydow, and D. Weiss, "Exploring linguistic features for Web spam detection: A preliminary study," in Proceedings of the Fourth International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 25-28, New York, NY, USA: ACM, 2008.

[191]

G. Price, "Google and Google bombing now included New Oxford American Dictionary," Retrieved June 1, 2009 from http://blog.searchenginewatch. com/blog/050516-184202, May 2005.

[192]

N. Provos, P. Mavrommatis, A. M. Rajab, and F. Monrose, "All your iFRAMEs point to us," in Proceedings of the 17th USENIX Security Symposium, pp. 1-15, Berkeley, CA, USA: USENIX Association, 2008.

[193]

N. Provos, D. McNamee, P. Mavrommatis, K. Wang, and N. Modadugu, "The ghost in the browser analysis of web-based malware," in Proceedings of the First Workshop on Hot Topics in Understanding Botnets (HotBots), 2007.

[194]

X. Qi and D. B. Davison, "Knowing a web page by the company it keeps," in Proceedings of the 15th ACM International Conference on Information and Knowledge Management (CIKM), pp. 228-237, New York, NY: ACM Press, November 2006.

[195]

X. Qi and D. B. Davison, "Web page classification: Features and algorithms," ACM Computing Surveys, vol. 41, no. 2, February 2009.

Digital Library

[196]

X. Qi, L. Nie, and D. B. Davison, "Measuring similarity to detect qualified links," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 49-56, May 2007.

[197]

R. J. Quinlan, C4.5: Programs for Machine Learning. San Mateo, CA: Morgan Kaufmann, 1993.

Digital Library

[198]

S. R. Rainwater, "Nigritude ultramarine FAQ," Retrieved June 1, 2009 from http://www.nigritudeultramarines.com/, 2005.

[199]

Y. Rasolofo and J. Savoy, "Term proximity scoring for keyword-based retrieval systems," in ECIR, pp. 207-218, 2003.

[200]

P. Resnick, K. Kuwabara, R. Zeckhauser, and E. Friedman, "Reputation systems," Communications of the ACM, vol. 43, no. 12, pp. 45-48, 2000.

Digital Library

[201]

M. Richardson, A. Prakash, and E. Brill, "Beyond PageRank: Machine learning for static ranking," in Proceedings of the 15th International Conference on World Wide Web (WWW), pp. 707-715, New York, NY, USA: ACM Press, May 2006.

[202]

G. Roberts and J. Rosenthal, "Downweighting tightly knit communities in World Wide Web rankings," Advances and Applications in Statistics (ADAS), vol. 3, pp. 199-216, 2003.

[203]

S. Robertson, S. Walker, M. M. Beaulieu, M. Gatford, and A. Payne, "Okapi at TREC-4," in NIST Special Publication 500-236: The Fourth Text REtrieval Conference (TREC-4), pp. 73-96, 1995.

[204]

G. Salton, A. Wong, and S. C. Yang, "A vector space model for automatic indexing," Communications of the ACM, vol. 18, no. 11, pp. 613-620, November 1975.

Digital Library

[205]

Y. Sato, T. Utsuro, Y. Murakami, T. Fukuhara, H. Nakagawa, Y. Kawada, and N. Kando, "Analysing features of Japanese splogs and characteristics of keywords," in Proceedings of the Fourth International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 33-40, New York, NY, USA: ACM, 2008.

[206]

C. Schmidt, "Page hijack: The 302 exploit, redirects and Google," http://clsc.net/research/google-302-page-hijack.htm, 2005.

[207]

F. Sebastiani, "Machine learning in automated text categorization," ACM Computing Surveys, vol. 34, no. 1, pp. 1-47, 2002.

Digital Library

[208]

D. Sheldon, "Manipulation of PageRank and Collective Hidden Markov Models," PhD thesis, Cornell University, 2009.

[209]

G. Shen, B. Gao, T.-Y. Liu, G. Feng, S. Song, and H. Li, "Detecting link spam using temporal information," in Proceedings of the Sixth IEEE International Conference on Data Mining (ICDM), December 2006.

[210]

N. Shrivastava, A. Majumder, and R. Rastogi, "Mining (social) network graphs to detect random link attacks," in Proceedings of the International Conference on Data Engineering (ICDE), IEEE CS Press, April 2008.

[211]

F. Silvestri, "Mining query logs: Turning search usage data into knowledge," Foundations and Trends in Information Retrieval, vol. 3, 2009.

[212]

A. Singhal, "Challenges in running a commercial search engine," Keynote presentation at SIGIR 2005, August 2005.

[213]

M. Sirivianos, X. Yang, and K. Kim, "FaceTrust: Assessing the credibility of online personas via social networks," Technical Report, Duke University, 2009. Retrieved 15 June 2009 from http://www.cs.duke.edu/~msirivia/ publications/facetrust-tech-report.pdf.

[214]

M. Sobek, "PR0 -- Google's PageRank 0 penalty," http://pr.efactory.de/ e-pr0.shtml, 2002.

[215]

A. Stassopoulou and D. M. Dikaiakos, "Web robot detection: A probabilistic reasoning approach," Computer Networks, vol. 53, no. 3, pp. 265-278, February 2009.

Digital Library

[216]

A.-J. Su, C. Y. Hu, A. Kuzmanovic, and C.-K. Koh, "How to improve your Google ranking: Myths and reality," in Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), pp. 50-57, Vol. 1, IEEE, 2010.

[217]

M. K. Svore, Q. Wu, C. J. C. Burges, and A. Raman, "Improving Web spam classification using rank-time features," in Proceedings of the Third International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 9-16, New York, NY, USA: ACM Press, 2007.

[218]

P.-N. Tan and V. Kumar, "Discovery of Web robot sessions based on their navigational patterns," Data Mining and Knowledge Discovery, vol. 6, no. 1, pp. 9-35, 2002.

Digital Library

[219]

E. Tardos and T. Wexler, "Network formation games and the potential function method," in Algorithmic Game Theory, (N. Nisan, T. Roughgarden, E. Tardos, and V. Vazirani, eds.), Cambridge University Press, 2007.

[220]

C. Tatum, "Deconstructing Google bombs: A breach of symbolic power or just a goofy prank?," First Monday, vol. 10, no. 10, October 2005.

[221]

A. Thomason, "Blog spam: A review," in Proceedings of Conference on Email and Anti-Spam (CEAS), August 2007.

[222]

A. Toffler, "The Third Wave," Bantam Books, 1980.

[223]

N. Tran, B. Min, J. Li, and L. Submaranian, "Sybil-resilient online content voting," in Proceedings of the 6th Symposium on Networked System Design and Implementation (NSDI), 2009.

[224]

T. Urvoy, E. Chauveau, P. Filoche, and T. Lavergne, "Tracking Web spam with HTML style similarities," ACM Transactions on the Web, vol. 2, no. 1, 2008.

Digital Library

[225]

T. Urvoy, T. Lavergne, and P. Filoche, "Tracking Web spam with hidden style similarity," in Proceedings of the Second International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), August 2006.

[226]

N. Vidyasaga, "India's secret army of online ad 'clickers'," The Times of India, May 2004.

[227]

L. A. von Ahn and L. Dabbish, "Labeling images with a computer game," in Proceedings of the Conference on Human Factors in Computing Systems (CHI), pp. 319-326, ACM Press, 2004.

[228]

K. Walsh and G. E. Sirer, "Fighting peer-to-peer spam and decoys with object reputation," in Proceedings of the ACM SIGCOMM Workshop on Economics of Peer-to-Peer systems (P2PECON), pp. 138-143, New York, NY, USA: ACM Press, 2005.

[229]

W. Wang, G. Zeng, M. Sun, H. Gu, and Q. Zhang, "EviRank: An evidence based content trust model for Web spam detection," in Proceedings of Workshop on Emerging Trends of Web Technologies and Applications WAIM/APWeb, pp. 299-307, 2007.

[230]

Y.-M. Wang, D. Beck, X. Jiang, and R. Roussev, "Automated web patrol with Strider HoneyMonkeys: Finding web sites that exploit browser vulnerabilities," in Proceedings of the Network and Distributed System Security Symposium (NDSS), February 2006.

[231]

Y.-M. Wang, M. Ma, Y. Niu, and H. Chen, "Spam double-funnel: Connecting Web spammers with advertisers," in Proceedings of the 16th International Conference on World Wide Web (WWW), pp. 291-300, New York, NY, USA: ACM Press, 2007.

[232]

S. Webb, "Automatic Identification and Removal of Low Quality Online Information," PhD thesis, College of Computing, Georgia Institute of Technology, December 2008.

[233]

S. Webb, J. Caverlee, and C. Pu, "Introducing the Webb spam corpus: Using email spam to identify Web spam automatically," in Proceedings of the Third Conference on Email and Anti-Spam (CEAS), July 2006.

[234]

S. Webb, J. Caverlee, and C. Pu, "Predicting Web spam with HTTP session information," in Proceeding of the 17th ACM Conference on Information and Knowledge Management (CIKM), pp. 339-348, New York, NY, USA: ACM, 2008.

[235]

H. I. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, 1999.

Digital Library

[236]

B. Wu, "Finding and Fighting Search Engine Spam," PhD thesis, Department of Computer Science and Engineering, Lehigh University, March 2007.

[237]

B. Wu and K. Chellapilla, "Extracting link spam using biased random walks from spam seed sets," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 37-44, New York, NY, USA: ACM Press, 2007.

[238]

B. Wu and D. B. Davison, "Cloaking and redirection: A preliminary study," in Proceedings of the 1st International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), 2005.

[239]

B. Wu and D. B. Davison, "Detecting semantic cloaking on the Web," in Proceedings of the 15th International World Wide Web Conference (WWW), pp. 819-828, ACM Press, 2006.

[240]

B. Wu and D. B. Davison, "Undue influence: Eliminating the impact of link plagiarism on Web search rankings," in Proceedings of The 21st ACM Symposium on Applied Computing (SAC), pp. 1099-1104, April 2006.

[241]

B. Wu and D. B. Davison, "Identifying link farm spam pages," in Special interest tracks and posters of the 14th International Conference on World Wide Web (WWW), pp. 820-829, New York, NY, USA: ACM Press, 2005.

[242]

B. Wu, V. Goel, and D. B. Davison, "Propagating trust and distrust to demote Web spam," in Workshop on Models of Trust for the Web (MTW), May 2006.

[243]

B. Wu, V. Goel, and D. B. Davison, "Topical TrustRank: Using topicality to combat Web spam," in Proceedings of the 15th International World Wide Web Conference (WWW), pp. 63-71, ACM Press, May 2006.

[244]

L. Xiong and L. Liu, "PeerTrust: Supporting reputation-based trust for peer-to-peer electronic communities," IEEE Transactions on Knowledge and Data Engineering, vol. 16, no. 7, pp. 843-857, 2004.

Digital Library

[245]

H. Yu, M. Kaminsky, B. P. Gibbons, and A. Flaxman, "SybilGuard: Defending against sybil attacks via social networks," in Proceedings of the ACM Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM), pp. 267-278, New York, NY, USA: ACM Press, 2006.

[246]

K. Yusuke, W. Atsumu, K. Takashi, B. B. Bahadur, and T. Toyoo, "On a referrer spam blocking scheme using Bayesian filter," Joho Shori Gakkai Shinpojiumu Ronbunshu, vol. 1, no. 13, pp. 319-324, In Japanese, 2005.

[247]

H. Zhang, A. Goel, R. Govindan, K. Mason, and B. V. Roy, "Making eigenvector-based reputation systems robust to collusion," in Proceedings of the Third Workshop on Web Graphs (WAW), pp. 92-104, Springer: Vol. 3243 of Lecture Notes in Computer Science, October 2004.

[248]

L. Zhang, Y. Zhang, Y. Zhang, and X. Li, "Exploring both content and link quality for anti-spamming," in Proceedings of the Sixth IEEE International Conference on Computer and Information Technology (CIT), IEEE Computer Society, 2006.

[249]

Y. Zhang and A. Moffat, "Some observations on user search behavior," Australian Journal of Intelligent Information Processing Systems, vol. 9, no. 2, pp. 1-8, 2006.

[250]

L. Zhao, Q. Jiang, and Y. Zhang, "From good to bad ones: Making spam detection easier," in Proceedings of the Eighth IEEE International Conference on Computer and Information Technology Workshops (CIT), IEEE Computer Society, 2008.

[251]

B. Zhou, "Mining page farms and its application in link spam detection," Master's thesis, Simon Fraser University, 2007.

[252]

B. Zhou and J. Pei, "Sketching landscapes of page farms," in Proceedings of the 7th SIAM International Conference on Data Mining (SDM), SIAM, April 2007.

[253]

B. Zhou, J. Pei, and Z. Tang, "A spamicity approach to Web spam detection," in Proceedings of the SIAM International Conference on Data Mining (SDM), April 2008.

[254]

D. Zhou, C. J. C. Burges, and T. Tao, "Transductive link spam detection," in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), pp. 21-28, New York, NY, USA: ACM Press, 2007.

[255]

C.-N. Ziegler and G. Lausen, "Propagation models for trust and distrust in social networks," Information Systems Frontiers, vol. 7, no. 4-5, pp. 337-358, December 2005.

Digital Library

[256]

R. P. Zimmermann, The Official PGP User's Guide. Cambridge, MA: MIT Press, 1995.

[257]

J. Zittrain, The Future of the Internet -- And How to Stop It. Yale University Press, April 2008.

Cited By

Nachimovsky HTennenholtz MRaiber FKurland OOosterhuis HBast HXiong C(2024)Ranking-Incentivized Document Manipulations for Multiple QueriesProceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3664190.3672516(61-70)Online publication date: 2-Aug-2024
https://dl.acm.org/doi/10.1145/3664190.3672516
Gupta SOosterhuis Hde Rijke MSerra ESpezzano F(2024)Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to RankProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679531(737-747)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679531
Liu YZhang RGuo Jde Rijke MHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Robust Information RetrievalProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3661380(3009-3012)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3661380
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cover image Foundations and Trends in Information Retrieval

Foundations and Trends in Information Retrieval Volume 4, Issue 5

May 2011

113 pages

ISSN:1554-0669

EISSN:1554-0677

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Now Publishers Inc.

Hanover, MA, United States

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Published: 01 May 2011

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Cited By

Nachimovsky HTennenholtz MRaiber FKurland OOosterhuis HBast HXiong C(2024)Ranking-Incentivized Document Manipulations for Multiple QueriesProceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3664190.3672516(61-70)Online publication date: 2-Aug-2024
https://dl.acm.org/doi/10.1145/3664190.3672516
Gupta SOosterhuis Hde Rijke MSerra ESpezzano F(2024)Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to RankProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679531(737-747)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679531
Liu YZhang RGuo Jde Rijke MHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Robust Information RetrievalProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3661380(3009-3012)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3661380
Liu YZhang RGuo Jde Rijke MFan YCheng XHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Multi-granular Adversarial Attacks against Black-box Neural Ranking ModelsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657704(1391-1400)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657704
Liu YZhang RGuo Jde Rijke MChen WFan YCheng XFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning MethodProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3614793(1647-1656)Online publication date: 21-Oct-2023
https://dl.acm.org/doi/10.1145/3583780.3614793
Vasilisky ZKurland OTennenholtz MRaiber FYoshioka MKiseleva JAliannejadi M(2023)Content-Based Relevance Estimation in Retrieval Settings with Ranking-Incentivized Document ManipulationsProceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3578337.3605124(205-214)Online publication date: 9-Aug-2023
https://dl.acm.org/doi/10.1145/3578337.3605124
Wu CZhang RGuo JDe Rijke MFan YCheng X(2023)PRADA: Practical Black-box Adversarial Attacks against Neural Ranking ModelsACM Transactions on Information Systems10.1145/357692341:4(1-27)Online publication date: 8-Apr-2023
https://dl.acm.org/doi/10.1145/3576923
Schultheiß S(2023)How search engine marketing influences user knowledge gainProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578297(475-478)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578297
Liu YZhang RGuo Jde Rijke MChen WFan YCheng XChen HDuh WHuang HKato MMothe JPoblete B(2023)Topic-oriented Adversarial Attacks against Black-box Neural Ranking ModelsProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591777(1700-1709)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3591777
Wu CZhang RGuo JFan YCheng X(2022)Are Neural Ranking Models Robust?ACM Transactions on Information Systems10.1145/353492841:2(1-36)Online publication date: 21-Dec-2022
https://dl.acm.org/doi/10.1145/3534928
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