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Nan Lin

Personal Details

First Name:Nan
Middle Name:
Last Name:Lin
Suffix:
RePEc Short-ID:pli1024
[This author has chosen not to make the email address public]

Affiliation

(50%) Shanghai University of Finance and Economics

Shanghai, China
http://www.shufe.edu.cn/

:


RePEc:edi:shufecn (more details at EDIRC)

(50%) School of International Business Administration
Shanghai University of Finance and Economics

Shanghai, China
http://sm.shufe.edu.cn/

:


RePEc:edi:smshucn (more details at EDIRC)

Research output

as
Jump to: Articles

Articles

  1. Nan Lin & Daifeng Li & Ying Ding & Bing He & Zheng Qin & Jie Tang & Juanzi Li & Tianxi Dong, 2012. "The dynamic features of Delicious, Flickr, and YouTube," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 139-162, January.
  2. Daifeng Li & Ying Ding & Cassidy Sugimoto & Bing He & Jie Tang & Erjia Yan & Nan Lin & Zheng Qin & Tianxi Dong, 2011. "Modeling topic and community structure in social tagging: The TTR-LDA-Community model," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(9), pages 1849-1866, September.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Daifeng Li & Ying Ding & Cassidy Sugimoto & Bing He & Jie Tang & Erjia Yan & Nan Lin & Zheng Qin & Tianxi Dong, 2011. "Modeling topic and community structure in social tagging: The TTR-LDA-Community model," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(9), pages 1849-1866, September.

    Cited by:

    1. Xiaoling Sun & Hongfei Lin, 2013. "Topical community detection from mining user tagging behavior and interest," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(2), pages 321-333, February.

More information

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