Tag: Mobile Phone Data rss


28 June 2017 / / Publications
Authors: Henry Navarro, Giovanna Miritello, Arturo Canales, Esteban Moro Journal: EPJ Data Science (2017) 6:31 LINK Abstract: Social networks are made out of strong and weak ties having very different structural and dynamical properties. But what features of human interaction build a strong tie? Here we approach this question from a practical way by finding what are the properties of social interactions that make ties more persistent and thus stronger to maintain social interactions in the future.
17 May 2013 / / Publications
Authors: Giovanna Miritello, Rubén Lara, and Esteban Moro Book: “Temporal Networks”, Springer, 2013. Series: Understanding Complex Systems. Holme, Petter; Saramaki, Jari (Eds.) **[PDF]((http://arxiv.org/pdf/1305.3865v1.pdf)** Summary Recent research has shown the deep impact of the dynamics of human interactions (or temporal social networks) on the spreading of information, opinion formation, etc. In general, the bursty nature of human interactions lowers the interaction between people to the extent that both the speed and reach of information diffusion are diminished.
09 April 2013 / / Publications
Authors: Giovanna Miritello, Rubén Lara, Manuel Cebrián and Esteban Moro Journal: Scientific Reports 3, 1950 (2013). LINK Abstract: Social connectivity is the key process that characterizes the structural properties of social networks and in turn processes such as navigation, influence or information diffusion. Since time, attention and cognition are inelastic resources, humans should have a predefined strategy to manage their social interactions over time. However, the limited observational length of existing human interaction datasets, together with the bursty nature of dyadic communications have hampered the observation of tie dynamics in social networks.
25 November 2010 / / Publications
Authors: Giovanna Miritello, Esteban Moro y Rubén Lara Journal: Physical Review E (Rapid Comm) 83, 045102 (2011). LINK | arXiv Abstract: We investigate the temporal patterns of human communication and its influence on the spreading of information in social networks. The analysis of mobile phone calls of 20 million people in one country shows that human communication is bursty and happens in group conversations. These features have opposite effects in information reach: while bursts hinder propagation at large scales, conversations favor local rapid cascades.