A Comparison of Social Bookmarking with Traditional Search

  • Beate Krause
  • Andreas Hotho
  • Gerd Stumme
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4956)

Abstract

Social bookmarking systems allow users to store links to internet resources on a web page. As social bookmarking systems are growing in popularity, search algorithms have been developed that transfer the idea of link-based rankings in the Web to a social bookmarking system’s data structure. These rankings differ from traditional search engine rankings in that they incorporate the rating of users.

In this study, we compare search in social bookmarking systems with traditional Web search. In the first part, we compare the user activity and behaviour in both kinds of systems, as well as the overlap of the underlying sets of URLs. In the second part, we compare graph-based and vector space rankings for social bookmarking systems with commercial search engine rankings.

Our experiments are performed on data of the social bookmarking system Del.icio.us and on rankings and log data from Google, MSN, and AOL. We will show that part of the difference between the systems is due to different behaviour (e.g. the concatenation of multi-word lexems to single terms in Del.icio.us), and that real-world events may trigger similar behaviour in both kinds of systems. We will also show that a graph-based ranking approach on folksonomies yields results that are closer to the rankings of the commercial search engines than vector space retrieval, and that the correlation is high in particular for the domains that are well covered by the social bookmarking system.

Keywords

social search folksonomies search engines ranking 

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References

  1. 1.
    Adar, E., Weld, D., Bershad, B., Gribble, S.: Why we search: Visualizing and predicting user behavior. In: Proc. WWW 2007, Banff, Canada, pp. 161–170 (2007)Google Scholar
  2. 2.
    Bao, S., Xue, G., Wu, X., Yu, Y., Fei, B., Su, Z.: Optimizing web search using social annotations. In: Proc. WWW 2007, Banff, Canada, pp. 501–510 (2007)Google Scholar
  3. 3.
    Bar-Ilan, J., Mat-Hassan, M., Levene, M.: Methods for comparing rankings of search engine results. Comput. Networks 50(10), 1448–1463 (2006)MATHCrossRefGoogle Scholar
  4. 4.
    Broder, A.Z.: A taxonomy of web search. SIGIR Forum 36(2), 3–10 (2002)CrossRefGoogle Scholar
  5. 5.
    Chatfield, C.: The analysis of time series: an introduction, 6th edn. CRC Press, Florida (2004)MATHGoogle Scholar
  6. 6.
    Chien, S., Immorlica, N.: Semantic similarity between search engine queries using temporal correlation. In: Proc. WWW 2005, pp. 2–11. ACM Press, New York (2005)CrossRefGoogle Scholar
  7. 7.
    Golder, S., Huberman, B.A.: The structure of collaborative tagging systems. Journal of Information Science 32(2), 198–208 (2006)CrossRefGoogle Scholar
  8. 8.
    Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Information retrieval in folksonomies: Search and ranking. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 411–426. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Ivorix. Sine-weighted moving average (2007), http://www.ivorix.com/en/products/tech/smooth/smooth.html
  10. 10.
    Krishna, A.M., Gummadi, P., Druschel, P.: Exploiting social networks for internet search. In: Proc. HotNets-V, pp. 79–84 (2006)Google Scholar
  11. 11.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: Bringing order to the web. In: Proc. WWW 1998, Brisbane, Australia, pp. 161–172 (1998)Google Scholar
  12. 12.
    Pass, G., Chowdhury, A., Torgeson, C.: A picture of search. In: Proc. 1st Intl. Conf. on Scalable Information Systems, ACM Press, New York (2006)Google Scholar
  13. 13.
    Vlachos, M., Meek, C., Vagena, Z., Gunopulos, D.: Identifying similarities, periodicities and bursts for online search queries. In: Proc. SIGMOD 2004, ACM Press, New York (2004)Google Scholar
  14. 14.
    Yanbe, Y., Jatowt, A., Nakamura, S., Tanaka, K.: Can social bookmarking enhance search in the web? In: Proc. JCDL 2007, pp. 107–116. ACM Press, New York (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Beate Krause
    • 1
    • 2
  • Andreas Hotho
    • 1
  • Gerd Stumme
    • 1
    • 2
  1. 1.Knowledge & Data Engineering GroupUniversity of KasselKasselGermany
  2. 2.Research Center L3SHannoverGermany

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