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      Do the Young Live in a "Smaller World" Than the Old? Age-Specific Degrees of Separation in a Large-Scale Mobile Communication Network

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          Abstract

          That any two persons are separated by a relatively small number of intermediary contacts -- the "small-world" phenomenon -- is a surprising but well established regularity in human social networks. To date, network science has ignored the question of whether the small world phenomenon manifests itself in similar ways across dyadic classes defined by individual traits, such as age or sex. To address this gap in the literature, we explore the phenomenon of "age-specific small worlds" by employing a mobile phone network built from billions of communication events approximating interaction patterns at a societal scale. We observe the average distance between any pair of users is 9.52, corresponding to nine-and-a-half degrees of separation. More importantly, we show that there is a systematic relationship between age and the average distance connecting that person to others, with some age groups falling below this average quantity while others falling above. Young people live in the "smallest world," being separated from other young people and their parent's generation via a comparatively small number of intermediaries. Older people live in the "least small world," being separated from their same age peers and their younger counterparts by a relatively large number of intermediaries. Middle age-people fall in between, being sociometrically close to both younger and older generations. However, there exists no significant difference of this age-effect on small world size between men and women. In all these results demonstrate that age-group heterogeneity of the small world can be traced to well-known social mechanisms affecting the way that age interacts with overall volume of connectivity and the relative prevalence of kin ties and non-kin ties, and may have important implications for our understanding of information cascades, diffusion phenomena, and the localized spread of fads and fashions.

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          Most cited references28

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          Understanding individual human mobility patterns

          Despite their importance for urban planning, traffic forecasting, and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited thanks to the lack of tools to monitor the time resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six month period. We find that in contrast with the random trajectories predicted by the prevailing Levy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time independent characteristic length scale and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent based modeling.
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            Core Discussion Networks of Americans

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              Classes of behavior of small-world networks

              Small-world networks are the focus of recent interest because they appear to circumvent many of the limitations of either random networks or regular lattices as frameworks for the study of interaction networks of complex systems. Here, we report an empirical study of the statistical properties of a variety of diverse real-world networks. We present evidence of the occurrence of three classes of small-world networks: (a) scale-free networks, characterized by a vertex connectivity distribution that decays as a power law; (b) broad-scale networks, characterized by a connectivity distribution that has a power-law regime followed by a sharp cut-off; (c) single-scale networks, characterized by a connectivity distribution with a fast decaying tail. Moreover, we note for the classes of broad-scale and single-scale networks that there are constraints limiting the addition of new links. Our results suggest that the nature of such constraints may be the controlling factor for the emergence of different classes of networks.
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                Author and article information

                Journal
                2016-06-23
                Article
                1606.07556
                ee9bb0cb-c199-4ea2-ab0c-9c0412ea0b5c

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                8 pages, 8 figures
                cs.SI physics.soc-ph

                Social & Information networks,General physics
                Social & Information networks, General physics

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