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RECAST: Telling Apart Social and Random Relationships in Dynamic Networks

Olmo Stancioli Vaz de Melo, Pedro and Viana, Aline and Fiore, Marco and Jaffrès-Runser, Katia and Le Moüel, Frédéric and Loureiro, Antonio A.F. and Addepalli, Lavanya and Chen, Guangshuo RECAST: Telling Apart Social and Random Relationships in Dynamic Networks. (2015) Performance Evaluation - Special Issue: Recent Advances in Modeling and Performance Evaluation in Wireless and Mobile Systems, vol. 87. pp. 19-36. ISSN 0166-5316

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Official URL: http://dx.doi.org/10.1016/j.peva.2015.01.005

Abstract

When constructing a social network from interactions among people (e.g., phone calls, encounters), a crucial task is to define the threshold that separates social from random (or casual) relationships. The ability to accurately identify social relationships becomes essential to applications that rely on a precise description of human routines, such as recommendation systems, forwarding strategies and opportunistic dissemination protocols. We thus propose a strategy to analyze users' interactions in dynamic networks where entities act according to their interests and activity dynamics. Our strategy, named Random rElationship ClASsifier sTrategy (RECAST), allows classifying users interactions, separating random ties from social ones. To that end, RECAST observes how the real system differs from an equivalent one where entities' decisions are completely random. We evaluate the effectiveness of the RECAST classification on five real-world user contact datasets collected in diverse networking contexts. Our analysis unveils significant differences among the dynamics of users' wireless interactions in the datasets, which we leverage to unveil the impact of social ties on opportunistic routing. We show that, for such specific purpose, the relationships inferred by RECAST are more relevant than, e.g., self-declared friendships on Facebook.

Item Type:Article
Additional Information:Thanks to Elsevier editor. The definitive version is available at http://www.sciencedirect.com The original PDF of the article can be found at: http://www.sciencedirect.com/science/article/pii/S0166531615000061
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Institut National de la Recherche en Informatique et en Automatique - INRIA (FRANCE)
Other partners > Institut National des Sciences Appliquées de Lyon - INSA (FRANCE)
Other partners > Polytechnic University of Valencia (SPAIN)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Universidade Federal de Minas Gerais - UFMG (BRAZIL)
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Deposited By: IRIT IRIT
Deposited On:03 Mar 2016 15:30

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