Abstract
A framework, the IGCV (Identification, Grouping, Clustering and Visualisation) framework, is described to support the temporal analysis of social network data. More specifically the identification and visualisation of "traffic movement" of patterns in such networks, and how such patterns change over time. A full description of the operation of IGCV is presented, together with an evaluation of its operation using a cattle movement network. © Springer-Verlag London Limited 2011.
Cite
CITATION STYLE
Nohuddin, P. N. E., Sunayama, W., Christley, R., Coenen, F., & Setzkorn, C. (2011). Trend mining and visualisation in social networks. In Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 269–282). Springer London. https://doi.org/10.1007/978-1-4471-2318-7_21
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