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.
Liste complète des métadonnées

Cited literature [34 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01150667
Contributor : Jason Vallet <>
Submitted on : Monday, May 11, 2015 - 4:31:02 PM
Last modification on : Thursday, January 11, 2018 - 6:20:17 AM
Document(s) archivé(s) le : Wednesday, April 19, 2017 - 8:54:07 PM

File

paper.pdf
Files produced by the author(s)

Identifiers

Citation

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⟩

Share

Metrics

Record views

637

Files downloads

178