A Visual Analytics Approach to Compare Propagation Models in Social Networks
April 10, 2015 Β· Declared Dead Β· π GaM
"No code URL or promise found in abstract"
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Authors
Jason Vallet, Hélène Kirchner, Bruno Pinaud, Guy Melançon
arXiv ID
1504.02612
Category
cs.SI: Social & Info Networks
Cross-listed
cs.LO
Citations
32
Venue
GaM
Last Checked
6 months ago
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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