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Social tags: meaning and suggestions

by: Fabian M. Suchanek, Milan Vojnovic, and Dinan Gunawardena

In: CIKM '08: Proceeding of the 17th ACM conference on Information and knowledge management New York, NY, USA: ACM (2008) , p. 223--232.

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URL:	http://portal.acm.org/citation.cfm?id=1458114
DOI:	10.1145/1458082.1458114

This paper aims to quantify two common assumptions about social tagging: 1 that tags are "meaningful" and 2 that the tagging process is influenced by tag suggestions. For 1, we analyze the semantic properties of tags and the relationship between the tags and the content of the tagged page. Our analysis is based on a corpus of search keywords, contents, titles, and tags applied to several thousand popular Web pages. Among other results, we find that the more popular tags of a page tend to be the more meaningful ones. For 2, we develop a model of how the influence of tag suggestions can be measured. From a user study with over 4,000 participants, we conclude that roughly one third of the tag applications may be induced by the suggestions. Our results would be of interest for designers of social tagging systems and are a step towards understanding how to best leverage social tags for applications such as search and information extraction.

BibTeX record

@inproceedings{suchanek2008social,
  abstract = {This paper aims to quantify two common assumptions about social tagging: (1) that tags are "meaningful" and (2) that the tagging process is influenced by tag suggestions. For (1), we analyze the semantic properties of tags and the relationship between the tags and the content of the tagged page. Our analysis is based on a corpus of search keywords, contents, titles, and tags applied to several thousand popular Web pages. Among other results, we find that the more popular tags of a page tend to be the more meaningful ones. For (2), we develop a model of how the influence of tag suggestions can be measured. From a user study with over 4,000 participants, we conclude that roughly one third of the tag applications may be induced by the suggestions. Our results would be of interest for designers of social tagging systems and are a step towards understanding how to best leverage social tags for applications such as search and information extraction.},
  added-at = {2009-05-15T15:52:03.000+0200},
  address = {New York, NY, USA},
  author = {Suchanek, Fabian M. and Vojnovic, Milan and Gunawardena, Dinan},
  biburl = {http://www.bibsonomy.org/bibtex/2732270af27da1046616415c8335382f6/jaeschke},
  booktitle = {CIKM '08: Proceeding of the 17th ACM conference on Information and knowledge management},
  doi = {http://doi.acm.org/10.1145/1458082.1458114},
  interhash = {1bca5a66a6a562258e0c0357545fed34},
  intrahash = {732270af27da1046616415c8335382f6},
  isbn = {978-1-59593-991-3},
  keywords = {folksonomy meaning recommender tag},
  location = {Napa Valley, California, USA},
  pages = {223--232},
  publisher = {ACM},
  timestamp = {2009-05-15T15:52:03.000+0200},
  title = {Social tags: meaning and suggestions},
  url = {http://portal.acm.org/citation.cfm?id=1458114},
  year = 2008
}

Endnote record

%0 Conference Paper
%1 suchanek2008social
%A Suchanek, Fabian M.
%A Vojnovic, Milan
%A Gunawardena, Dinan
%B CIKM '08: Proceeding of the 17th ACM conference on Information and knowledge management
%@ 978-1-59593-991-3
%C New York, NY, USA
%D 2008
%I ACM
%K 
%P 223--232
%T Social tags: meaning and suggestions
%R http://doi.acm.org/10.1145/1458082.1458114
%U http://portal.acm.org/citation.cfm?id=1458114
%X This paper aims to quantify two common assumptions about social tagging: (1) that tags are "meaningful" and (2) that the tagging process is influenced by tag suggestions. For (1), we analyze the semantic properties of tags and the relationship between the tags and the content of the tagged page. Our analysis is based on a corpus of search keywords, contents, titles, and tags applied to several thousand popular Web pages. Among other results, we find that the more popular tags of a page tend to be the more meaningful ones. For (2), we develop a model of how the influence of tag suggestions can be measured. From a user study with over 4,000 participants, we conclude that roughly one third of the tag applications may be induced by the suggestions. Our results would be of interest for designers of social tagging systems and are a step towards understanding how to best leverage social tags for applications such as search and information extraction.

BibSonomy :: publication ::

Social tags: meaning and suggestions

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Abstract

BibTeX record

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