Username   Password       Forgot your password?  Forgot your username? 


Volume 14 - 2018

No.1 January 2018
No.1 January 2018
No.3 March 2018
No.3 March 2018
No.4 April 2018
No.4 April 2018
No.5 May 2018
No.5 May 2018
No.6 June 2018
No.6 June 2018
No.7 July 2018
No.7 July 2018

Volume 13 - 2017

No.4 July 2017
No.4 July 2017
No.5 September 2017
No.5 September 2017
No.7 November 2017
No.7 November 2017
No.8 December 2017
No.8 December 2017

Volume 12 - 2016

Volume 11 - 2015

Volume 10 - 2014

Volume 9 - 2013

Volume 8 - 2012

Volume 7 - 2011

Volume 6 - 2010

Volume 5 - 2009

Volume 4 - 2008

Volume 3 - 2007

Volume 2 - 2006


Identifying Opinion Leaders with Improved Weighted LeaderRank in Online Learning Communities

Volume 14, Number 2, February 2018, pp. 193-201
DOI: 10.23940/ijpe.18.02.p1.193201

Ling Luoa, You Yanga, Zizhong Chenb, Yan Weia


aComputer and Information Science Department, Chongqing Normal University, Chongqing, 401331, China

bDepartment of Computer Science and Engineering, University of California, Riverside, 92521, United State



Opinion leaders play a crucial role in closely interconnecting groups and help achieve better group performances in online learning communities. Weighted LeaderRank is superior to other methods in identifying opinion leaders, but there are some limitations in its weighted mechanism. This study further optimizes the weighted mechanism of weighted LeaderRank by introducing users’ initial comprehensive influence and the number of user interactivity. Experimental results show that the improved weighted LeaderRank algorithm can improve the accuracy of opinion leader identification in online learning communities compared with the other two typical algorithms.


References: 26

  1. S. M. Aghdam, N. J. Navimipour, “Opinion Leaders Selection in the Social Networks Based on Trust Relationships Propagation,” Karbala International Journal of Modern Science, vol. 2, no. 2, pp. 88–97, 2016
  2. P. Bonacich, “Factoring and Weighting Approaches to Status Scores and Clique Identification,” J Math Sociol, vol. 2, pp. 113-120, 1972
  3. R. S. Burt, M. J Minor, R D Alba, “Applied network analysis: A Methodological Introduction,” Sage Publications Beverly Hills. 1983
  4. D. Chen, L. Lü, M. S. Shang, Y. C. Zhang, T. Zhou, “Identifying Influential Nodes in Complex Networks,” Physica A. vol. 391, pp. 1777–1787, 2012
  5. J. B. Carson, P. E. Tesluk, J. A. Marrone, “Shared Leadership in Teams: An Investigation of Antecedent Conditions and Performance,” IEEE Engineering Management Review, vol. 44, no. 3, pp. 86-103, 2016
  6. M. I. Dascalu, C. N. Bodea, M. Lytras, et al, “Improving E-learning Communities Through Optimal Composition of Multidisciplinary Learning Groups,” Computers in Human Behavior, vol. 30, pp. 362-371, 2014
  7. L. C. Freeman, “Centrality in Social Networks Conceptual Clarification,” Social Network, vol 1, pp. 215–239, 1979
  8. L. C. Freeman, S. P. Borgatti, D. R. White, “Centrality in Valued Graphs: A measure of Betweenness Based on Network Flow,” Social Network, vol. 13, pp. 141–154, 1991
  9. Arian Hafezalkotob, Ashkan Hafezalkotob, “Extended MULTIMOORA Method Based on Shannon Entropy Weight for Materials Selection,” Journal of Industrial Engineering International, vol, 12, no. 1, pp. 1-13, 2016
  10. P. Hage, F. Harary, “Eccentricity and Centrality in Networks,” Social Network, vol. 17, pp. 57–63, 1995
  11. P. Jomsri, S. Sanguansintukul, W. Choochaiwattana. “CiteRank: Combination Similarity and Static Ranking with Research Paper Searching,” International Journal of Internet Technology and Secured Transactions, vol. 3, no. 2, pp. 161-177, 2011
  12. M. Kitsak, L. K. Gallos, S. Havlin, F. Liljeros, L. Muchnik. “Identification of Influential Spreaders in Complex Networks,” Nature physics, vol 6, p:888–893, 2010
  13. L. Lü, Y. C. Zhang, C. H. Yeung, T. Zhou, “Leaders in Social Networks, the Delicious Case,” PLoS One, vol. 6, no. 6, pp. e21202, 2011
  14. P. F. Lazarsfeld, B. Berelson, H. Gaudet, “The People’s Choice: How the Voter Makes up his Mind in a Presidential Campaign. New York: Duell,” Sloan and Pierce, 1968
  15. Qian Li, Tao Zhou, Linyuan Lü, et al, “Identifying Influential Spreaders by Weighted Leader Rank,” Physica A: Statistical Mechanics and Its Applications, vol. 404, pp. 47-55, 2014
  16. L. Page, S. Brin, R. Motwani, T. Winograd. “The PageRank Citation Ranking: Bringing Order to the Web,” Technical Report Stanford Infolab, 1999
  17. R. K. Purvanova, J. E. Bono, “E-leadership and Virtual Teams,” Organizational dynamics, vol. 32, no. 4, pp.362-376, 2003
  18. Y. Qi, F. Wen, K. Wang, L. Li, S. Singh, “A Fuzzy Comprehensive Evaluation and Entropy Weight Decision-making Based Method for Power Network Structure Assessment,” International Journal of Engineering, Science and Technology, vol. 2, no. 5, pp. 92-99, 2010
  19. Xiaolong Reng, Linyuan Lv, “Review of the Sorting Method of Important Nodes in Network,” Chinese Science Bulletin, vol. 59, no. 13, pp. 15-37, 2014
  20. H. Y. Sung, G. J. Hwang, “A Collaborative Game-based Learning Approach to Improving Students' Learning Performance in Science Courses”, Computers & Education, vol. 63, pp. 43–51, 2013
  21. B. D. Wever, H. V. Keer, T. Schellens, et al. “Roles as a Structuring tool in Online Discussion Groups: the Differential Impact of Different Roles on Social Knowledge Construction,” Computers in Human Behavior, vol. 26, pp. 516–523, 2010
  22. J. Weng, E. P. Lim, J. Jiang, Q. He, “Twitterrank: Finding Topic-sensitive Influential Twitterers,” Proceedings of the Third ACM International Conference on Web Search and Data Mining, pp. 261-270, 2010
  23. Y. Wu, Lu-lu, Ma, Mao Lin, Hong-tao Liu, “Discovery Algorithm of Opinion Leaders Based on User Influence,” Journal of Chinese Computer System, vol. 36, no. 3, pp. 163-167, 2015
  24. Erjia Yan, Ying Ding, “Discovering Author Impact: A Page Rank Perspective,” Information Processing and Management, vol. 7, pp. 125–134, 2011
  25. G. Zhang, F. Bao, Z. Liu, “Research on Process Modeling of Information Dissemination Based on Social Network,” International Journal of Multimedia and Ubiquitous Engineering, vol.11, no. 7, pp. 261-270, 2016
  26. S. Zha, C. L. Ottendorfer, “Effects of Peer-led Online Asynchronous Discussion on Undergraduate Students’ Cognitive Achievement,” The American Journal of Distance Education, vol. 25, pp. 238–253, 2011


Please note : You will need Adobe Acrobat viewer to view the full articles.Get Free Adobe Reader

Download this file (IJPE-2018-02-01.pdf)IJPE-2018-02-01.pdf[Identifying Opinion Leaders with Improved Weighted LeaderRank in Online Learning Communities]525 Kb


Prev Next

Data Packet Processing Model based on Multi-Core Architecture

Xian Zhang, Dong Yin, Taiguo Qu, Jia Liu, and Yiwen Liu

Read more

Mixed Weighted KNN for Imbalanced Datasets

Qimin Cao, Lei La, Hongxia Liu, and Si Han

Read more

Query Expansion based on Naive Bayes and Semantic Similarity

Zhiyun Zheng, Mengyao Yu, Ning Wang, Xingjin Zhang, Chunyang Ruan, and Dun Li

Read more

Automated Collaborative Analysis System of Rockburst Mechanism based on Big Data

Yu Zhang, Hongwei Ding, Yange Wang, Fuqiang Ren, Yongzhen Li, and Zhaoyong Lv

Read more

EOR of Spontaneous Imbibition by Surfactant Solution for Tight Oil Reservoirs

Anqi Shen, Yikun Liu, Shuang Liang, Fengjiao Wang, Bo Cai, and Yuebin Gao

Read more

Dynamic Community Mining based on Behavior Prediction

Xiao Chen, Xinzhuan Hu, Xiao Pan, and Jingfeng Guo

Read more

Lithium-ion Power Batteries SOC Estimation based on PCA

Haiying Wang, Yuran Wang, Zhilin Yao, and Zhilong Yu

Read more
This site uses encryption for transmitting your passwords.