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Creating tag hierarchies for effective navigation in social media
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Conference on Information and Knowledge Management archive
Proceeding of the 2008 ACM workshop on Search in social media table of contents
Napa Valley, California, USA
SESSION: Social network analysis table of contents
Pages 75-82  
Year of Publication: 2008
ISBN:978-1-60558-258-0
Authors
K. Selçuk Candan  Arizona State University, Tempe, AZ, USA
Luigi Di Caro  Universita' di Torino, Torino, Italy
Maria Luisa Sapino  Universita' di Torino, Torino, Italy
Sponsors
ACM: Association for Computing Machinery
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

In social media, such as blogs, since the content naturally evolves over time, it is hard or in many cases impossible to organize the content for effective navigation. Thus, one commonly has to resort to simple tools, such as tags and tag clouds, for presenting frequently used keywords to users to provide them at least some high level idea about the content of a given set of social media entries. Most visualizations of tag clouds vary the sizes of the fonts to differentiate important tags from those that are less important. We propose an alternative "contextual-layout" method, TMine, for analyzing and presenting tags that are extracted from textual content. In TMine tags are first mapped onto a latent semantic space. Then, TMine analyzes the relationships between tags relying on an extended boolean interpretation of the semantic space. The tag cloud is condensed into a hierarchy in a way that captures contextual relationships between tags: in particular, descendant terms in the hierarchy occur within the context defined by the ancestor terms. This provides a mechanism for navigation within the tag space as well as for classification of the text documents based on the contextual structure implied by the tags.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
K. Selçuk Candan: colleagues
Luigi Di Caro: colleagues
Maria Luisa Sapino: colleagues