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Animating the development of _Social Networks_ over time 
using a dynamic extension of multidimensional scaling 

Loet Leydesdorff, Thomas Schank, Andrea Scharnhorst, & Wouter De Nooy

The animation of network visualizations poses technical and theoretical
challenges. Rather stable patterns are required before the mental map
enables a user to make inferences over time. In order to enhance stability,
we developed an extension of stress-minimization with developments over
time. This dynamic layouter is no longer based on linear interpolation
between independent static visualizations, but change over time is used as a
parameter in the optimization. Because of our focus on structural change
versus stability the attention is shifted from the relational graph to the
latent eigenvectors of matrices. The approach is illustrated with animations
for the journal citation environments of Social Networks, the (co-)author
networks in the carrying community of this journal, and the topical
development using relations among its title words. Our results are also
compared with animations based on PajekToSVGAnim and SoNIA.

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Loet Leydesdorff, 
Amsterdam School of Communications Research (ASCoR), 
Kloveniersburgwal 48, 1012 CX Amsterdam


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