Predictors of Users’ Willingness to Personalize Web Search

  • Arjumand Younus
  • Colm O’Riordan
  • Gabriella Pasi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8132)


Personalized Web search offers a promising solution to the task of user-tailored information-seeking; however, one of the reasons why it is not widely adopted by users is due to privacy concerns. Over the past few years social networking services (SNS) have re-shaped the traditional paradigm of information-seeking. People now tend to simultaneously make use of both Web search engines and social networking services when faced with an information need. In this paper, using data gathered in a user survey, we present an analysis of the correlation between the users’ willingness to personalize Web search and their social network usage patterns. The participants’ responses to the survey questions enabled us to use a regression model for identifying the relationship between SNS variables and willingness to personalize Web search. We also performed a follow-up user survey for use in a support vector machine (SVM) based prediction framework. The prediction results lead to the observation that SNS features such as a user’s demographic factors (such as age, gender, location), a user’s presence or absence on Twitter and Google+, amount of activity on Twitter and Google+ along with the user’s tendency to ask questions on social networks are significant predictors in characterising users who would be willing to opt for personalized Web search results.


Support Vector Machine Privacy Concern Social Networking Service User Survey Implicit User 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Boyd, D.M., Hargittai, E.: Facebook privacy settings: Who cares? First Monday 15(8) (2010)Google Scholar
  2. 2.
    Carmel, D., Zwerdling, N., Guy, I., Ofek-Koifman, S., Har’el, N., Ronen, I., Uziel, E., Yogev, S., Chernov, S.: Personalized social search based on the user’s social network. In: CIKM 2009, pp. 1227–1236. ACM, New York (2009)Google Scholar
  3. 3.
    DiSalvo, D.: Are social networks messing with your head? Scientific American Mind 20, 48–55 (2010)CrossRefGoogle Scholar
  4. 4.
    Dou, Z., Song, R., Wen, J.-R.: A large-scale evaluation and analysis of personalized search strategies. In: WWW 2007, pp. 581–590. ACM, New York (2007)Google Scholar
  5. 5.
    Heymann, P., Koutrika, G., Garcia-Molina, H.: Can social bookmarking improve web search? In: WSDM 2008, pp. 195–206. ACM, New York (2008)Google Scholar
  6. 6.
    Horowitz, D., Kamvar, S.D.: The anatomy of a large-scale social search engine. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010, pp. 431–440. ACM, New York (2010)CrossRefGoogle Scholar
  7. 7.
    Karat, C.-M., Brodie, C., Karat, J.: Usable privacy and security for personal information management. Commun. ACM 49(1), 56–57 (2006)CrossRefGoogle Scholar
  8. 8.
    Kobsa, A.: Privacy-enhanced web personalization. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 628–670. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Morris, M.R., Jaime, T., Panovich, K.: A Comparison of Information Seeking Using Search Engines and Social Networks. In: ICWSM 2010, pp. 291–294 (2010)Google Scholar
  10. 10.
    Morris, M.R., Teevan, J., Panovich, K.: What do people ask their social networks, and why?: a survey study of status message q & a behavior. In: CHI 2010, pp. 1739–1748. ACM, New York (2010)Google Scholar
  11. 11.
    Sackmann, S., Strüker, J., Accorsi, R.: Personalization in privacy-aware highly dynamic systems. Commun. ACM 49(9), 32–38 (2006)CrossRefGoogle Scholar
  12. 12.
    Shen, X., Tan, B., Zhai, C.: Implicit user modeling for personalized search. In: CIKM 2005, pp. 824–831. ACM, New York (2005)Google Scholar
  13. 13.
    Shen, X., Tan, B., Zhai, C.: Privacy protection in personalized search. SIGIR Forum 41(1), 4–17 (2007)CrossRefGoogle Scholar
  14. 14.
    Stutzman, F.D.: Networked Information Behavior in Life Transition. PhD thesis, The University of North Carolina at Chapel Hill (2011)Google Scholar
  15. 15.
    Teevan, J., Dumais, S.T., Horvitz, E.: Personalizing search via automated analysis of interests and activities. In: SIGIR 2005, ACM, pp. 449–456. New York (2005)Google Scholar
  16. 16.
    Teevan, J., Morris, M.R.: Exploring the complementary roles of social networks and search engines. In: HCIC 2012 (2012)Google Scholar
  17. 17.
    Wang, Q., Jin, H.: Exploring online social activities for adaptive search personalization. In: CIKM 2010, pp. 999–1008. ACM, New York (2010)Google Scholar
  18. 18.
    Zhao, W.X., Jiang, J., Weng, J., He, J., Lim, E.-P., Yan, H., Li, X.: Comparing twitter and traditional media using topic models. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 338–349. Springer, Heidelberg (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Arjumand Younus
    • 1
    • 2
  • Colm O’Riordan
    • 1
  • Gabriella Pasi
    • 2
  1. 1.Computational Intelligence Research Group, Information TechnologyNational University of IrelandGalwayIreland
  2. 2.Information Retrieval Lab, Informatics, Systems and CommunicationUniversity of Milan BicoccaMilanItaly

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