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A Visual Analytics Approach to Compare Propagation Models in Social Networks

Abstract : Numerous propagation models describing social influence in social networks can be found in the literature. This makes the choice of an appropriate model in a given situation difficult. Selecting the most relevant model requires the ability to objectively compare them. This comparison can only be made at the cost of describing models based on a common formalism and yet independent from them. We propose to use graph rewriting to formally describe propagation mechanisms as local transformation rules applied according to a strategy. This approach makes sense when it is supported by a visual analytics framework dedicated to graph rewriting. The paper first presents our methodology to describe some propagation models as a graph rewriting problem. Then, we illustrate how our visual analytics framework allows to interactively manipulate models, and underline their differences based on measures computed on simulation traces.
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Contributor : Jason Vallet Connect in order to contact the contributor
Submitted on : Monday, May 11, 2015 - 4:31:02 PM
Last modification on : Friday, February 4, 2022 - 3:24:56 AM
Long-term archiving on: : Wednesday, April 19, 2017 - 8:54:07 PM


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Jason Vallet, Hélène Kirchner, Bruno Pinaud, Guy Melançon. A Visual Analytics Approach to Compare Propagation Models in Social Networks. Graphs as Models, Apr 2015, London, United Kingdom. ⟨10.4204/EPTCS.181.5⟩. ⟨hal-01150667⟩



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