Abstract
Given a social network, identifying significant nodes from the network is highly desirable in many applications. In different networks formed by diverse kinds of social connections, the definitions of what are significant nodes differ with circumstances. In the literature, most previous works generally focus on expertise finding in specific social networks. In this paper, we aim to propose a general node ranking model that can be adopted to satisfy a variety of service demands. We devise an unsupervised learning method that produces the ranking list of top-k significant nodes. The characteristic of this method is that it can generate different ranking lists when diverse sets of features are considered. To demonstrate the real application of the proposed method, we design the system DblpNET that is an author ranking system based on the co-author network of DBLP computer science bibliography. We discuss further extensions and evaluate DblpNET empirically on the public DBLP dataset. The evaluation results show that the proposed method can effectively apply to real-world applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zhang, J., Ackerman, M.S., Adamic, L.: Expertise Networks in Online Communities: Structure and Algorithms. In: Proc. of the 16th International Conference on World Wide Web (WWW), pp. 221–230 (2007)
Noll, M.G., Au Yeung, C., Gibbins, N., Meinel, C., Shadbolt, N.: Telling Experts from Spammers: Expertise Ranking in Folksonomies. In: Proc. of the 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 612–619 (2009)
Balog, K., Azzopardi, L., de Rijke, M.: Formal Models for Expert Finding in Enterprise Corpora. In: Proc. of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 43–50 (2006)
Dom, B., Eiron, I., Cozzi, A., Zhang, Y.: Graph-Based Ranking Algorithms for Email Expertise Analysis. In: Proc. of the 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, pp. 42–48 (2003)
Zhang, J., Tang, J., Li, J.: Expert Finding in a Social Network. In: Kotagiri, R., Radha Krishna, P., Mohania, M., Nantajeewarawat, E. (eds.) DASFAA 2007. LNCS, vol. 4443, pp. 1066–1069. Springer, Heidelberg (2007)
Ley, M.: The DBLP (Digital Bibliography and Library Project) Computer Science Bibliography, http://www.informatik.uni-trier.de/~ley/db/
Liu, X., Bollen, J., Nelson, M.L., de Sompel, H.V.: Co-authorship Networks in the Digital Library Research Community. In: Information Processing and Management, pp. 1462–1480 (2005)
Nascimento, M.A., Sander, J., Pound, J.: Analysis of SIGMOD’s Co-Authorship Graph. ACM SIGMOD Record, 8–10 (2003)
Newman, M.E.J.: Coauthorship Networks and Patterns of Scientific Collaboration. Proc. of the National Academy of Sciences, 5200–5205 (2004)
Zaïane, O.R., Chen, J., Goebel, R.: Mining Research Communities in Bibliographical Data. In: Zhang, H., Spiliopoulou, M., Mobasher, B., Giles, C.L., McCallum, A., Nasraoui, O., Srivastava, J., Yen, J. (eds.) WebKDD 2007. LNCS, vol. 5439, pp. 59–76. Springer, Heidelberg (2009)
Zhou, D., Orshanskiy, S.A., Zha, H., Giles, C.L.: Co-Ranking Authors and Documents in a Heterogeneous Network. In: Proc. of the 7th IEEE International Conference on Data Mining (ICDM), pp. 739–744 (2007)
Tseng, C.Y., Chen, M.S.: Significant Nodes Identification in the Co-author Network of DBLP, http://cytseng.no-ip.org/dblpnet.php
Newman, M.E.J.: The Structure of Scientific Collaboration Networks. Proc. of the National Academy of Sciences, 404–409 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tseng, CY., Chen, MS. (2012). Significant Node Identification in Social Networks. In: Cao, L., Huang, J.Z., Bailey, J., Koh, Y.S., Luo, J. (eds) New Frontiers in Applied Data Mining. PAKDD 2011. Lecture Notes in Computer Science(), vol 7104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28320-8_39
Download citation
DOI: https://doi.org/10.1007/978-3-642-28320-8_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28319-2
Online ISBN: 978-3-642-28320-8
eBook Packages: Computer ScienceComputer Science (R0)