Information Organization Patterns from Online Users in a Social Network

Chengzhi Zhang; Hua Zhao; Xuehua Chi; Shuitian Ma

doi:10.5771/0943-7444-2019-2-90

Contents
- Chapter Expand | CollapseAuthorsPage
- I–II Titelei/Inhaltsverzeichnis I–II
- 77–103 Articles 77–103
  - 77–89 Creating a Taxonomy of Earthquake Disaster Response and Recovery for Online Earthquake Information Management Li Yang, Yejun Wu Li Yang, Yejun Wu 77–89
  - 90–103 Information Organization Patterns from Online Users in a Social Network Chengzhi Zhang, Hua Zhao, Xuehua Chi, Shuitian Ma Chengzhi Zhang, Hua Zhao, Xuehua Chi, Shuitian Ma 90–103
- 104–146 Reviews of Concepts in KO 104–146
  - 104–121 Automatic Subject Indexing of Text Koraljka Golub Koraljka Golub 104–121
  - 122–146 Interoperability Marcia Lei Zeng Marcia Lei Zeng 122–146
- 147–154 Review 147–154
  - Semantic Perception: How the Illusion of a Common Language Arises and Persists, Jody Azzouni. New York: Oxford University Press, 2013. ISBN 9780199967407. 2015. ISBN 9780190275549. Ontology Without Borders, Jody Azzouni. New York, NY: Oxford University Press. ISBN 9780190622558. Matthew Kelly Matthew Kelly
- 154–154 Erratum 154–154
- 155–155 Books recently published 155–155
- 156–157 Impressum 156–157
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KO KNOWLEDGE ORGANIZATION , page 90 - 103

Information Organization Patterns from Online Users in a Social Network

Autoren

Chengzhi Zhang Hua Zhao Xuehua Chi Shuitian Ma

DOI
- doi.org/10.5771/0943-7444-2019-2-90
- ISSN: 0943-7444
- ISSN online: 2942-3309
Abstract

Recent years have seen the rise of user-generated contents (UGCs) in online social media. Diverse UGC sources and information overload are making it increasingly difficult to satisfy personalized information needs. To organize UGCs in a user-centered way, we should not only map them based on textual topics but also link them with users and even user communities. We propose a multi-dimensional framework to organize information by connecting UGCs, users, and user communities. First, we use a topic model to generate a topic hierarchy from UGCs. Second, an author-topic model is applied to learn user interests. Third, user communities are detected through a label propagation algorithm. Finally, a multi-dimensional information organization pattern is formulated based on similarities among the topic hierarchies of UGCs, user interests, and user communities. The results reveal that: 1) our proposed framework can organize information from multiple sources in a user-centered way; 2) hierarchical topic structures can provide comprehensive and in-depth topics for users; and, 3) user communities are efficient in helping people to connect with others who have similar interests.
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