Giovanna Miritello, Rubén Lara, and Esteban Moro
Chapter in the book ”Temporal Networks”, Springer, 2013. Series: Understanding Complex Systems. Holme, Petter; Saramaki, Jari (Eds.) [pdf]
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. Using a large database of 20 million users of mobile phone calls we show evidence this effect is not homogeneous in the social network but in fact, there is a large correlation between this effect and the social topological structure around a given individual. In particular, we show that social relations of hubs in a network are relatively weaker from the dynamical point than those that are poorer connected in the information diffusion process. Our results show the importance of the temporal patterns of communication when analyzing and modeling dynamical process on social networks.
In our last (just accepted) paper “Limited communication capacity unveils strategies for human interaction” [pdf] we have found that we humans have different social strategies when we communicate/interact with people. Specifically, the sociability of a person (the total number of contacts in a time interval) which is usually taken as the connectivity in the social network is actually the result of two different human features:
- Social capacity: the number of relationships humans can maintain opened and which is limited
- Social activity: the number of relationships human form and destroy as a consequence of their daily tasks, family, events, etc.
Social capacity and activity are very heterogenous and while most individuals have small capacity and activity, some might have large values for those characteristics. The ratio between these characteristics of human interaction determines the social strategy:
- Social keepers: these people have a small social activity compared to their social capacity, that is, they interact mostly with the same people in a time interval and form/destroy a small number of ties.
- Social explorers: the opposite strategy, meaning that most of the interactions of these people are form and destroyed rapidly while keeping a very small number of stable connections.
- Social balanced: most of the people have a balance social strategy in which the number of form/destroy interactions is proportional to their capacity.
To show how these strategies look like, we have produce the following videos where you can see the tie dynamics around a social explorer and a social keeper (red nodes) for a period of 7 months. Note that if you aggregate the activity of these two people over those 7 months, the will have the same connectivity. But clearly their instantaneous network is very different!
So, what do you think is your social strategy? Are you a social explorer or a social keeper?
Note: these videos are produced using R and the igraph library. Learn how to make them in my post here
Giovanna Miritello, Rubén Lara, Manuel Cebrián and Esteban Moro
arXiv:1304.1979, preprint (2013) [link]
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. Here we develop a method for the detection of tie activation/deactivation, and apply it to a large longitudinal, cross-sectional communication dataset (≈19 months, ≈ 20 million people). Contrary to the perception of ever-growing connectivity, we observe that individuals exhibit a finite communication capacity, which limits the number of ties they can maintain active. In particular we find that men have an overall higher communication capacity than women and that this capacity decreases gradually for both sexes over the lifespan of individuals (16-70 years). We are then able to separate communication capacity from communication activity, revealing a diverse range of tie activation patterns, from stable to exploratory. We find that, in simulation, individuals exhibiting exploratory strategies display longer time to receive information spreading in the network those individuals with stable strategies. Our principled method to determine the communication capacity of an individual allows us to quantify how strategies for human interaction shape the dynamical evolution of social networks.