| Member Profile : Dominik Benz |
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 | Contact Information | Address: -Map Me-
Dominik Benz
University of Kassel
Wilhelmshöher Allee 73
Kassel, Hessen, Germany 34131
Phone : +495618046266
E-mail : benz@cs.uni-kassel.de
Website : http://www.kde.cs.uni-kassel.de/benz
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| Sunbelt XXX - June 29 to July 04, 2010 - Riva del Garda Fierecongressi | | Abstract : Social Bookmarking Systems: Verbosity Improves Semantics |
Recent research provides evidence for the presence of emergent
semantics in collaborative tagging systems. While several methods
have been proposed, little is known about the factors that influence
the evolution of semantic structures in these systems. A natural
hypothesis is that the quality of the emergent semantics depends on
the pragmatics of tagging: Users with certain usage patterns might
contribute more to the resulting semantics than others.
We propose several measures which enable a pragmatic differentiation
of taggers by their degree of contribution to emerging semantic
structures. We distinguish between "categorizers", who typically use
a small set of tags as a replacement for hierarchical classification
schemes, and "describers", who are annotating resources with a
wealth of freely associated, descriptive keywords. To study our
hypothesis, we apply semantic similarity measures to 64 different
partitions of a real-world and large-scale folksonomy containing
different ratios of categorizers and describers. Our results not
only show that 'verbose' taggers are most useful for the emergence
of tag semantics, but also that a subset containing only 40 % of
the most 'verbose' taggers can produce results that match and even
outperform the semantic precision obtained from the whole dataset.
Moreover, the results suggest that there exists a causal link
between the pragmatics of tagging and resulting emergent semantics.
This work is relevant for designers and analysts of tagging systems
interested (i) in fostering the semantic development of their
platforms, (ii) in identifying users introducing "semantic noise",
and (iii) in learning ontologies. |
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