A Comparison of Social Bookmarking with Traditional Search

  • Beate Krause
  • Andreas Hotho
  • Gerd Stumme
Conference paper

DOI: 10.1007/978-3-540-78646-7_12

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4956)
Cite this paper as:
Krause B., Hotho A., Stumme G. (2008) A Comparison of Social Bookmarking with Traditional Search. In: Macdonald C., Ounis I., Plachouras V., Ruthven I., White R.W. (eds) Advances in Information Retrieval. ECIR 2008. Lecture Notes in Computer Science, vol 4956. Springer, Berlin, Heidelberg

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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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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