Complex networks & Human mobility
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[1301.2464] Time as a limited resource: Communication Strategy in Mobile Phone Networks


Via giovanna miritello
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giovanna miritello's comment, January 14, 2013 1:04 PM
We used a large database of 9 billion calls from 20 million mobile users to examine the relationships between aggregated time spent on the phone, personal network size, tie strength and the way in which users distributed their limited time across their network (disparity). Compared to those with smaller networks, those with large networks did not devote proportionally more time to communication and had on average weaker ties (as measured by time spent communicating). Further, there were not substantially different levels of disparity between individuals, in that mobile users tend to distribute their time very unevenly across their network, with a large proportion of calls going to a small number of individuals. Together, these results suggest that there are time constraints which limit tie strength in large personal networks, and that even high levels of mobile communication do not fundamentally alter the disparity of time allocation across networks.
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Approaching the Limit of Predictability in Human Mobility : Scientific Reports : Nature Publishing Group

Approaching the Limit of Predictability in Human Mobility : Scientific Reports : Nature Publishing Group | Complex networks & Human mobility | Scoop.it
In this study we analyze the travel patterns of 500,000 individuals in Cote d'Ivoire using mobile phone call data records.
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Rescooped by Alejandro Llorente from Papers
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Human mobility and time spent at destination: Impact on spatial epidemic spreading

Host mobility plays a fundamental role in the spatial spread of infectious diseases. Previous theoretical works based on the integration of network theory into the metapopulation framework have shown that the heterogeneities that characterize real mobility networks favor the propagation of epidemics. Nevertheless, the studies conducted so far assumed the mobility process to be either Markovian or non-Markovian with a fixed traveling time scale. Available statistics however show that the time spent by travelers at destination is characterized by wide fluctuations, ranging between a single day up to several months. Such varying length of stay crucially affects the chance and duration of mixing events among hosts and may therefore have a strong impact on the spread of an emerging disease. Here, we present an analytical and computational study of epidemic processes on a complex subpopulation network where travelers have memory of their origin and spend a heterogeneously distributed time interval at their destination. Through analytical calculations and numerical simulations we show that the heterogeneity of the length of stay alters the expression of the threshold between local outbreak and global invasion, and, moreover, it changes the epidemic behavior of the system in case of a global outbreak. Additionally, our theoretical framework allows us to study the effect of changes in the traveling behavior in response to the infection, by considering a scenario in which sick individuals do not leave their home location. Finally, we compare the results of our non-Markovian framework with those obtained with a classic Markovian approach and find relevant differences between the two, in the estimate of the epidemic invasion potential, as well as of the timing and the pattern of its spatial spread.

 

Human mobility and time spent at destination: Impact on spatial epidemic spreading
Chiara Poletto, Michele Tizzoni, Vittoria Colizza

http://arxiv.org/abs/1309.6618


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