Viral spreading of daily information in online social networks

We explain a possible mechanism of an information spreading on a network which spreads extremely far from a seed node, namely the viral spreading. On the basis of a model of the information spreading in an online social network, in which the dynamics is expressed as a random multiplicative process of the spreading rates, we will show that the correlation between the spreading rates enhances the chance of the viral spreading, shifting the tipping point at which the spreading goes viral.

[1]  Esteban Moro Egido,et al.  Branching Dynamics of Viral Information Spreading , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Jon M. Kleinberg,et al.  Tracing information flow on a global scale using Internet chain-letter data , 2008, Proceedings of the National Academy of Sciences.

[3]  Jari Saramäki,et al.  Path lengths, correlations, and centrality in temporal networks , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Jari Saramäki,et al.  Temporal Networks , 2011, Encyclopedia of Social Network Analysis and Mining.

[5]  L. da F. Costa,et al.  A generalized approach to complex networks , 2006 .

[6]  Esteban Moro,et al.  Impact of human activity patterns on the dynamics of information diffusion. , 2009, Physical review letters.

[7]  M. Gerstein,et al.  The Spread of Scientific Information: Insights from the Web Usage Statistics in PLoS Article-Level Metrics , 2011, PloS one.

[8]  Matthew O Jackson,et al.  Using selection bias to explain the observed structure of Internet diffusions , 2010, Proceedings of the National Academy of Sciences.

[9]  A. Barabasi,et al.  Impact of non-Poissonian activity patterns on spreading processes. , 2006, Physical review letters.

[10]  Vittorio Loreto,et al.  Ring structures and mean first passage time in networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

[12]  Tatsuro Kawamoto.  A stochastic model of the tweet diffusion on the Twitter network , 2012, ArXiv.

[13]  Mark E. J. Newman,et al.  Ego-centered networks and the ripple effect , 2001, Soc. Networks.

[14]  T. E. Harris,et al.  The Theory of Branching Processes. , 1963 .

[15]  Alexei Vazquez,et al.  Polynomial growth in branching processes with diverging reproductive number. , 2006, Physical review letters.

[16]  Ulrik Brandes,et al.  Social Networks , 2013, Handbook of Graph Drawing and Visualization.

[17]  Jari Saramäki,et al.  Small But Slow World: How Network Topology and Burstiness Slow Down Spreading , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  M. Newman.  Spread of epidemic disease on networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Fang Wu,et al.  Novelty and collective attention , 2007, Proceedings of the National Academy of Sciences.

[20]  Filipi Nascimento Silva,et al.  Hierarchical Characterization of Complex Networks , 2004, cond-mat/0412761.