The Micro-Blogging Network Leading Group Recognition Algorithm

Li Li Dong; Ke Yang; Xiang Zhang

doi:10.4028/www.scientific.net/AMM.519-520.164

Paper Titles

A Novel Response Time-Driven Replica Selection Approach for Cloud Computing
p.146

A Secure Mobile Payments Protocol Based on ECC
p.151

A Security Routing Protocol Based on Convergence Degree and Trust
p.155

A Trust System Design for Future SCADA Network Security
p.160

The Micro-Blogging Network Leading Group Recognition Algorithm
p.164

The Design and Implementation of an Optimized MPTCP Data Scheduling Algorithm
p.170

The Design of PMP-AODV Routing Protocol in Wireless Mesh Network
p.177

An Attribute Mapping Technique for Secure Interoperation in Multi-Domain Environments
p.181

An Authentication Scheme Based on the Light-Weight Rainbow Signature for Wireless Sensor Network
p.185

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 519-520The Micro-Blogging Network Leading Group...

The Micro-Blogging Network Leading Group Recognition Algorithm

Abstract:

Based on the analysis and research of micro-blogging network transmission of information, the transmission of information model is constructed. By studying the network model, a small group of core users of the network information dissemination play a guiding role. To solve the problem that the research of micro-blogging user influence ranking can only ranking order given its influence, but not determine which user play a guiding role in transmission of information, LeadersRank algorithm based on the idea of personalized PageRank algorithm is proposed, and the algorithm is applied to the real micro-blogging data to identify the leading group, the experimental results prove the feasibility and effectiveness of the algorithm.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 519-520)

Pages:

164-169

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.519-520.164

Citation:

Cite this paper

Online since:

February 2014

Authors:

Li Li Dong, Ke Yang, Xiang Zhang

Keywords:

LeadersRank, Leading Group, Micro-Blogging, PageRank

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] YANG Liang, LIN Yuan, LIN Hongfei. Micro-Blog Hot Event Detection Based on Emotion Distribution[J]. Journal of Chinese Information Processing, 2012. 1.

Google Scholar

[2] A. Java，X. Song, T. Finin, etal. Why we twitter: understanding microblogging usage and communities. [C]/Proceedings of the 9thWebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Net-work Analysis, 2007: 56-65.

DOI: 10.1145/1348549.1348556

Google Scholar

[3] Weng. J, Lim. E, Jiang.J. etal. Twitterrank: Finding Topic－Sensitive Influential Twitterers．In Proceedings of the 3rd ACM internationalconference on Web search and data mining．ACM，2010，261－270.

DOI: 10.1145/1718487.1718520

Google Scholar

[4] WEN Kunmei, XU Shuai, LI Ruixuan, GU Xiwu, LI Yuhua. Survey of Microblog and Chinese Microblog Information Processing [J]. Journal of Chinese Information Processing, 2012. 6.

Google Scholar

[5] M. Cha, Haddadi,F. Benevenuto K.P. Gum-mad. Measuring user influence on twitter: the million follower fallacy[C]/Proceedings of the 4th International AAAI Conference on Weblogs and Social Media, (2010).

DOI: 10.1609/icwsm.v4i1.14033

Google Scholar

[6] P. Boldi, M. Santini, M. Vigna, PageRank: functional dependencies, ACMTrans-actions on Information Systems 27 (2009) 1–23. Article 19.

DOI: 10.1145/1629096.1629097

Google Scholar