A network approach to topic summary and knowledge discovery in social tagging

This doctoral research focuses on studying the semantic relations between social tags, items and content creators through co-occurrence analysis, social network analysis and information visualization, thus revealing the role played by social tags in representing and classifying contents and creators, and implications they might have for facilitating information seeking practice, particularly knowledge discovery and information summary, and as a result, helping the design of information retrieval and browsing interface. A user study is conducted to evaluate the effectiveness of visual constructions based on similarity and network analysis for several tasks that they can be used to support. Both network analysis and user study suggest that tag/author networks contain strong community structures that are algorithmically detectable and semantically relevant.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Library & Information Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Xiang, Xin

Contributors dc:contributor

• Heidorn, P. Bryan
• Smith, Linda C.
• Unsworth, John M.
• Zhai, ChengXiang

• Social tagging
• Complex network
• Tag
• Folksonomy
• Visualization
• Tag cloud
• Small world

Statement dc:rights

• Copyright 2011 Xin Xiang

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/26138

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/26138