Visualization methods for longitudinal social networks and stochastic actor-oriented modeling. Brandes, U., Indlekofer, N., & Mader, M. Social Networks, 34(3):291--308, July, 2012. ![Visualization methods for longitudinal social networks and stochastic actor-oriented modeling [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex As a consequence of the rising interest in longitudinal social networks and their analysis, there is also an increasing demand for tools to visualize them. We argue that similar adaptations of state-of-the-art graph-drawing methods can be used to visualize both, longitudinal networks and predictions of stochastic actor-oriented models (SAOMs), the most prominent approach for analyzing such networks. The proposed methods are illustrated on a longitudinal network of acquaintanceship among university freshmen.
@article{brandes_visualization_2012,
title = {Visualization methods for longitudinal social networks and stochastic actor-oriented modeling},
volume = {34},
issn = {0378-8733},
url = {http://www.sciencedirect.com/science/article/pii/S0378873311000347},
doi = {10.1016/j.socnet.2011.06.002},
abstract = {As a consequence of the rising interest in longitudinal social networks and their analysis, there is also an increasing demand for tools to visualize them. We argue that similar adaptations of state-of-the-art graph-drawing methods can be used to visualize both, longitudinal networks and predictions of stochastic actor-oriented models (SAOMs), the most prominent approach for analyzing such networks. The proposed methods are illustrated on a longitudinal network of acquaintanceship among university freshmen.},
number = {3},
urldate = {2012-05-23},
journal = {Social Networks},
author = {Brandes, Ulrik and Indlekofer, Natalie and Mader, Martin},
month = jul,
year = {2012},
keywords = {Dynamic network visualization, Longitudinal social networks, Model fit, Stochastic actor-oriented models},
pages = {291--308}
}
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