We study a social network consisting of over 10(4) individuals, with a degree distribution exhibiting two power scaling regimes separated by a critical degree k(crit), and a power law relation between degree and local clustering. We introduce a growing random model based on a local interaction mechanism that reproduces the observed scaling features and their exponents. We suggest that the double power law originates from two very different kinds of networks that are simultaneously present in the human social network.
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