IDEAS home Printed from https://ideas.repec.org/a/bla/jinfst/v64y2013i2p321-333.html

Topical community detection from mining user tagging behavior and interest

Author

Listed:
  • Xiaoling Sun
  • Hongfei Lin

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:jinfst:v:64:y:2013:i:2:p:321-333
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/asi.22740
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    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 American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(9), pages 1849-1866, September.
    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.
    3. Andrea Lancichinetti & Filippo Radicchi & José J Ramasco & Santo Fortunato, 2011. "Finding Statistically Significant Communities in Networks," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-18, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yunhong Xu & Dehu Yin & Duanning Zhou, 2019. "Investigating Users’ Tagging Behavior in Online Academic Community Based on Growth Model: Difference between Active and Inactive Users," Information Systems Frontiers, Springer, vol. 21(4), pages 761-772, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wu, Jianshe & Zhang, Long & Li, Yong & Jiao, Yang, 2016. "Partition signed social networks via clustering dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 568-582.
    2. Gregory, Steve, 2012. "Ordered community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2752-2763.
    3. de Arruda, Guilherme F. & Costa, Luciano da Fontoura & Rodrigues, Francisco A., 2012. "A complex networks approach for data clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6174-6183.
    4. Eustace, Justine & Wang, Xingyuan & Cui, Yaozu, 2015. "Overlapping community detection using neighborhood ratio matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 510-521.
    5. Kirsten Martinus & Thomas Sigler & Iacopo Iacopini & Ben Derudder, 2021. "The brokerage role of small states and territories in global corporate networks," Growth and Change, Wiley Blackwell, vol. 52(1), pages 12-28, March.
    6. Ivan Blekanov & Svetlana S. Bodrunova & Askar Akhmetov, 2021. "Detection of Hidden Communities in Twitter Discussions of Varying Volumes," Future Internet, MDPI, vol. 13(11), pages 1-17, November.
    7. Thang N. Dinh & Nam P. Nguyen & Md Abdul Alim & My T. Thai, 2015. "A near-optimal adaptive algorithm for maximizing modularity in dynamic scale-free networks," Journal of Combinatorial Optimization, Springer, vol. 30(3), pages 747-767, October.
    8. Fang, Wenyi & Wang, Xin & Liu, Longzhao & Wu, Zhaole & Tang, Shaoting & Zheng, Zhiming, 2022. "Community detection through vector-label propagation algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    9. Jesús Arroyo & Elizaveta Levina, 2022. "Overlapping Community Detection in Networks via Sparse Spectral Decomposition," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 1-35, June.
    10. Garza, Sara E. & Schaeffer, Satu Elisa, 2019. "Community detection with the Label Propagation Algorithm: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    11. Wu, Zhihao & Lin, Youfang & Wan, Huaiyu & Tian, Shengfeng & Hu, Keyun, 2012. "Efficient overlapping community detection in huge real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2475-2490.
    12. Sun, Peng Gang & Hu, Jingqi & Wu, Xunlian & Zhang, Han & Quan, Yining & Miao, Qiguang, 2025. "Graph reconstruction model for enhanced community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 664(C).
    13. Sun, Peng Gang & Wu, Xunlian & Quan, Yining & Miao, Qiguang, 2022. "Influence percolation method for overlapping community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    14. Liu, Qiang & Liu, Caihong & Wang, Jiajia & Wang, Xiang & Zhou, Bin & Zou, Peng, 2017. "Evolutionary link community structure discovery in dynamic weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 370-388.
    15. Andrea Flori & Simone Giansante & Claudia Girardone & Fabio Pammolli, 2021. "Banks’ business strategies on the edge of distress," Annals of Operations Research, Springer, vol. 299(1), pages 481-530, April.
    16. Carlo Piccardi, 2011. "Finding and Testing Network Communities by Lumped Markov Chains," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-13, November.
    17. Greg Morrison & L Mahadevan, 2012. "Discovering Communities through Friendship," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    18. Jiang, Yawen & Jia, Caiyan & Yu, Jian, 2013. "An efficient community detection method based on rank centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2182-2194.
    19. Franke, R., 2016. "CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 384-408.
    20. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2015. "Epidemic spreading on complex networks with overlapping and non-overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 171-182.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jinfst:v:64:y:2013:i:2:p:321-333. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.