Novel Epistemic and Predictive Heuristic for Semantic and Dynamic Social Networks Analysis

Christophe Thovex, Francky Trichet

Laboratory of Computer Sciences (LINA, UMR-CNRS 6241), University of Nantes, Nantes, France.

DOI: 10.4236/sn.2014.33021                

Abstract

Using Kripke semantics, we have identified and reduced an epistemic incompleteness in the metaphor commonly employed in Social Networks Analysis (SNA), which basically compares information flows with current flows in advanced centrality measures. Our theoretical approach defines a new paradigm for the semantic and dynamic analysis of social networks including shared content. Based on our theoretical findings, we define a semantic and predictive model of dynamic SNA for Enterprises Social Networks (ESN), and experiment it on a real dataset.

Keywords

Graph, Analysis, Interdisciplinary, Modal, Logic, Semantics, Social, Networks

Conflicts of Interest

The authors declare no conflicts of interest.

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