To improve existing social bookmarking systems and to design
new ones, researchers and practitioners need to understand how to
evaluate tagging behavior. In this paper, we analyze over two
years of data from CiteULike, a social bookmarking system for
tagging academic papers. We propose six tag metrics—tag
growth, tag reuse, tag non-obviousness, tag discrimination, tag
frequency, and tag patterns—to understand the characteristics of a
social bookmarking system. Using these metrics, we suggest
possible design heuristics to implement a social bookmarking
system for CiteSeer, a popular online scholarly digital library for
computer science. We believe that these metrics and design
heuristics can be applied to social bookmarking systems in other
domains.
%0 Conference Paper
%1 farooq2007evaluating
%A Farooq, Umer
%A Kannampallil, Thomas G.
%A Song, Yang
%A Ganoe, Craig H.
%A Carroll, John M.
%A Giles, C. Lee
%B GROUP '07: Proceedings of the 2007 international ACM conference on Conference on supporting group work
%C New York, NY, USA
%D 2007
%I ACM
%K behavior evaluation heuristics metrics mt tagging
%P 351--360
%R http://doi.acm.org/10.1145/1316624.1316677
%T Evaluating tagging behavior in social bookmarking systems: metrics and design heuristics
%U http://portal.acm.org/citation.cfm?id=1316677&coll=Portal&dl=GUIDE&CFID=9767993&CFTOKEN=86305662
%X To improve existing social bookmarking systems and to design
new ones, researchers and practitioners need to understand how to
evaluate tagging behavior. In this paper, we analyze over two
years of data from CiteULike, a social bookmarking system for
tagging academic papers. We propose six tag metrics—tag
growth, tag reuse, tag non-obviousness, tag discrimination, tag
frequency, and tag patterns—to understand the characteristics of a
social bookmarking system. Using these metrics, we suggest
possible design heuristics to implement a social bookmarking
system for CiteSeer, a popular online scholarly digital library for
computer science. We believe that these metrics and design
heuristics can be applied to social bookmarking systems in other
domains.
%@ 978-1-59593-845-9
@inproceedings{farooq2007evaluating,
abstract = {To improve existing social bookmarking systems and to design
new ones, researchers and practitioners need to understand how to
evaluate tagging behavior. In this paper, we analyze over two
years of data from CiteULike, a social bookmarking system for
tagging academic papers. We propose six tag metrics—tag
growth, tag reuse, tag non-obviousness, tag discrimination, tag
frequency, and tag patterns—to understand the characteristics of a
social bookmarking system. Using these metrics, we suggest
possible design heuristics to implement a social bookmarking
system for CiteSeer, a popular online scholarly digital library for
computer science. We believe that these metrics and design
heuristics can be applied to social bookmarking systems in other
domains.},
added-at = {2009-11-24T08:23:05.000+0100},
address = {New York, NY, USA},
author = {Farooq, Umer and Kannampallil, Thomas G. and Song, Yang and Ganoe, Craig H. and Carroll, John M. and Giles, C. Lee},
biburl = {https://www.bibsonomy.org/bibtex/277a3808c4891bbc7a2ba66bf186a978e/ghp09},
booktitle = {GROUP '07: Proceedings of the 2007 international ACM conference on Conference on supporting group work},
doi = {http://doi.acm.org/10.1145/1316624.1316677},
interhash = {ddd15789387831719c26828f98fc3d74},
intrahash = {77a3808c4891bbc7a2ba66bf186a978e},
isbn = {978-1-59593-845-9},
keywords = {behavior evaluation heuristics metrics mt tagging},
location = {Sanibel Island, Florida, USA},
pages = {351--360},
publisher = {ACM},
timestamp = {2009-11-24T08:28:40.000+0100},
title = {Evaluating tagging behavior in social bookmarking systems: metrics and design heuristics},
url = {http://portal.acm.org/citation.cfm?id=1316677&coll=Portal&dl=GUIDE&CFID=9767993&CFTOKEN=86305662},
year = 2007
}