D2SNet: Dynamics of diffusion and dynamic human behaviour in social networks

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.

[1]  Thilo Gross,et al.  Epidemic dynamics on an adaptive network. , 2005, Physical review letters.

[2]  D. Watts,et al.  Multiscale, resurgent epidemics in a hierarchical metapopulation model. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Martine Collard,et al.  Diffusion in Dynamic Social Networks: Application in Epidemiology , 2011, DEXA.

[4]  Madhav V. Marathe,et al.  Epidemiology and Wireless Communication: Tight Analogy or Loose Metaphor? , 2008, BIOWIRE.

[5]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[6]  D. Watts The “New” Science of Networks , 2004 .

[7]  A. Klovdahl,et al.  Social networks and the spread of infectious diseases: the AIDS example. , 1985, Social science & medicine.

[8]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[9]  W. O. Kermack,et al.  A contribution to the mathematical theory of epidemics , 1927 .

[10]  Sameep Mehta,et al.  A study of rumor control strategies on social networks , 2010, CIKM.

[11]  S. N. Dorogovtsev,et al.  Evolution of networks , 2001, cond-mat/0106144.

[12]  J. A. Barnes Class and Committees in a Norwegian Island Parish , 1954 .

[13]  Chunju Tseng,et al.  Incorporating Geographical Contacts into Social Network Analysis for Contact Tracing in Epidemiology: A Study on Taiwan SARS Data , 2007, BioSurveillance.

[14]  R. May,et al.  Population biology of infectious diseases: Part II , 1979, Nature.

[15]  Jari Saramäki,et al.  A comparative study of social network models: Network evolution models and nodal attribute models , 2008, Soc. Networks.

[16]  Daniel A. McFarland,et al.  Dynamic Network Visualization1 , 2005, American Journal of Sociology.

[17]  R. Christley,et al.  Infection in social networks: using network analysis to identify high-risk individuals. , 2005, American journal of epidemiology.

[18]  N. Christakis,et al.  Social Network Sensors for Early Detection of Contagious Outbreaks , 2010, PloS one.

[19]  Alessandro Vespignani,et al.  Epidemic modeling in metapopulation systems with heterogeneous coupling pattern: theory and simulations. , 2007, Journal of theoretical biology.

[20]  W. Edmunds,et al.  Dynamic social networks and the implications for the spread of infectious disease , 2008, Journal of The Royal Society Interface.

[21]  M. Newman,et al.  Network theory and SARS: predicting outbreak diversity , 2004, Journal of Theoretical Biology.

[22]  Daryl J. Daley,et al.  Epidemic Modelling: An Introduction , 1999 .

[23]  O Mason,et al.  Graph theory and networks in Biology. , 2006, IET systems biology.

[24]  Albert-László Barabási,et al.  Linked: The New Science of Networks , 2002 .

[25]  Stefan Bornholdt,et al.  Dynamics of social networks , 2003, Complex..

[26]  R. Albert,et al.  The large-scale organization of metabolic networks , 2000, Nature.

[27]  Réka Albert,et al.  Disease Dynamics in a Dynamic Social Network. , 2010, Physica A.

[28]  Martina Morris,et al.  Epidemiology and Social Networks: , 1993 .

[29]  Marcel Salathé,et al.  Dynamics and Control of Diseases in Networks with Community Structure , 2010, PLoS Comput. Biol..

[30]  R. Chambers,et al.  Family and social network , 1964 .

[31]  Nicolas Vidot,et al.  Social network analysis in epidemiology: Current trends and perspectives , 2011, 2011 FIFTH INTERNATIONAL CONFERENCE ON RESEARCH CHALLENGES IN INFORMATION SCIENCE.

[32]  Sharon L. Milgram,et al.  The Small World Problem , 1967 .

[33]  J. Kleinberg Computing: the wireless epidemic. , 2007, Nature.

[34]  Madhav V. Marathe,et al.  EpiSimdemics: an efficient algorithm for simulating the spread of infectious disease over large realistic social networks , 2008, HiPC 2008.

[35]  Sajal K. Das,et al.  Epidemic Models, Algorithms, and Protocols in Wireless Sensor and Ad Hoc Networks , 2008, Algorithms and Protocols for Wireless Sensor Networks.

[36]  Alessandro Vespignani,et al.  Network science , 2007, Annu. Rev. Inf. Sci. Technol..

[37]  Maria A. Kazandjieva,et al.  A high-resolution human contact network for infectious disease transmission , 2010, Proceedings of the National Academy of Sciences.

[38]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..