Research Paper: “Testing Assumptions About Social Tagging Systems: A Case Study of the Social Tagging System BibSonomy”

The following paper was recently shared on arXiv.

Title

Testing Assumptions about Social Tagging Systems: A Case Study of the Social Tagging System BibSonomy

Authors

Stephan Doerfel
University of Kassel
Daniel Zoller
University of Würzburg
Philipp Singer
Technical University Graz
Thomas Niebler
University of Würzburg
Andreas Hotho
University of Würzburg
Markus Strohmaier
University of Koblenz-Landau and GESIS

Source

via arXiv

Abstract

Social tagging systems have established themselves as an important part in today’s web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics.
Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions – e.g., is a tagging system really social? – by examining live log data gathered from the real-world public social tagging system BibSonomy.
Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.

Direct to Full Text Paper (12 pages; PDF)
See Also: Visit the BibSonomy Web Site
See Also: Related Publications by Stephan Doerfel

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