Synonyms
Glossary
- IA-EC:
-
Incremental adaptation-driven evolving clustering
- MD-EC:
-
Milestones’ detection-driven evolving clustering
- SM-EC:
-
Sequential mapping-driven evolving clustering
- TS-EC:
-
Temporal smoothing-driven evolving clustering
Definition
Social graphs In the current Web 2.0 or social Web era, users’ intensive engagement in social networking and content sharing applications results in the formation of a massive amount of new associations daily among the actors involved. The types of such associations vary, depending on the application at hand, and may correspond to either explicit or implicit relationships invoked by users’ actions.
Introduction
Associations formed in the context of social networking applications are often multiway; i.e., they involve multiple entities (e.g., user A commenting on post P of user B) and are more precisely captured in a generalized graph structure (i.e., hypergraph) with its (hyper)edges connecting more than two...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bazzi M, Porter MA, Williams S, McDonald M, Fenn DJ, Howison SD (2016) Community detection in temporal multilayer networks, with an application to correlation networks. Multiscale Model Simul 14(1):1–41
Chakrabarti D, Kumar R, Tomkins A (2006) Evolutionary clustering. In: Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining (KDD’06), Philadelphia. ACM, New York, pp 554–560
Dagnino GB, Levanti G, Destri AML (2016) Structural dynamics and intentional governance in strategic interorganizational network evolution: a multilevel approach. Organ Stud 37(3):349–373
Domingue J, Lasierra N, Fensel A, van Kasteren T, Strohbach M, Thalhammer A (2016) Big data analysis. In: New horizons for a data-driven economy. Springer International Publishing, Cham, pp 63–86
Fortunato S, Hric D (2016) Community detection in networks: a user guide. Phys Rep 659:1–44
Giatsoglou M, Vakali A (2012) Capturing social data evolution via graph clustering. IEEE Internet Comput (Preprint). https://doi.org/10.1109/MIC.2012.24
Giatsoglou M, Chatzakou D, Vakali A (2015) User communities evolution in microblogs: a public awareness barometer for real world events. World Wide Web 18(5):1269–1299
Hilbert M, Oh P, Monge P (2016) Evolution of what? A network approach for the detection of evolutionary forces. Soc Netw 47:38–46
Klašnja-Milićević A, Vesin B, Ivanović M, Budimac Z, Jain LC (2017) Folksonomy and tag-based recommender systems in E-Learning environments. In: E-Learning systems. Springer International Publishing, pp 77–112
Leiva LA, Vidal E (2013) Warped K-Means: an algorithm to cluster sequentially-distributed data. Inf Sci 237:196–210
Lin Y-R, Sun J, Castro P, Konuru R, Sundaram H, Kelliher A (2009) MetaFac: community discovery via relational hypergraph factorization. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining (KDD’09), Paris. ACM, New York, pp 527–536
Ning H, Xu W, Chi Y, Gong Y, Huang TS (2010) Incremental spectral clustering by efficiently updating the Eigen-system. Pattern Recognit 43(1):113–127
Palla G, Barabási A-L, Vicsek T (2007) Quantifying social group evolution. Nature 446(7136):664–667
Sun J, Faloutsos C, Papadimitriou S, Yu PS (2007) GraphScope: parameter-free mining of large time-evolving graphs. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining (KDD’07), San Jose. ACM, New York, pp 687–696
Sun J, Tao D, Papadimitriou S, Yu PS, Faloutsos C (2008) Incremental tensor analysis: theory and applications. ACM Trans Knowl Discov Data (TKDD) 2(3):11
Tang L, Liu H, Zhang J (2011) Identifying evolving groups in dynamic multi-mode networks. IEEE Trans Knowl Data Eng 18:72–85
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media LLC, part of Springer Nature
About this entry
Cite this entry
Vakali, A. (2018). Evolving Social Graph Clustering. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_47
Download citation
DOI: https://doi.org/10.1007/978-1-4939-7131-2_47
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-7130-5
Online ISBN: 978-1-4939-7131-2
eBook Packages: Computer ScienceReference Module Computer Science and Engineering