untitled
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<responseDate>2018-01-15T18:36:28Z</responseDate>
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<identifier>oai:HAL:hal-00786164v1</identifier>
<datestamp>2017-12-21</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>D2SNet: Dynamics of diffusion and dynamic human behaviour in social networks</title>
<creator>Stattner, Erick</creator>
<creator>Collard, Martine</creator>
<creator>Vidot, Nicolas</creator>
<contributor>Laboratoire de Mathématiques Informatique et Applications (LAMIA) ; Université des Antilles et de la Guyane (UAG)</contributor>
<description>International audience</description>
<source>ISSN: 0747-5632</source>
<source>EISSN: 0747-5632</source>
<source>Computers in Human Behavior</source>
<publisher>Elsevier</publisher>
<identifier>hal-00786164</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00786164</identifier>
<source>https://hal.archives-ouvertes.fr/hal-00786164</source>
<source>Computers in Human Behavior, Elsevier, 2013, 29 (2), pp.496-509. 〈10.1016/j.chb.2012.06.004〉</source>
<identifier>DOI : 10.1016/j.chb.2012.06.004</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chb.2012.06.004</relation>
<language>en</language>
<subject>[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>In this paper, we present an original and formal framework, the D2SNet model designed to combine both the social network evolution and the diffusion dynamics among individuals. We have conducted experiments on three social networks that show identical characteristics as real social networks. A formal definition of the model is provided and we describe its implementation in a simulation tool. We represent human behaviors and information dissemination strategies by standard and synthetic scheme. In a first step, we study the impact of network growing strategies only and we highlight important parameters such as the evolution speed and mainly the kind of strategies that favour or not the spread. Then we study a more complete evolution strategy that involves link creation and deletion. We provide a deep analysis on the impact of each parameter such as evolution speed, creation and deletion probabilities and dynamic human behaviors on the diffusion amplitude and coverage. Our study gives a novel and useful insight in the diffusion process in a dynamic context.</description>
<date>2013</date>
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