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Social networks have many counter-intuitive properties, including the"friendship paradox" that states, on average, your friends have more friendsthan you do. Recently, a variety of other paradoxes were demonstrated in onlinesocial networks. This paper explores the origins of these network paradoxes.Specifically, we ask whether they arise from mathematical properties of thenetworks or whether they have a behavioral origin. We show that sampling fromheavy-tailed distributions always gives rise to a paradox in the mean, but notthe median. We propose a strong form of network paradoxes, based on utilizingthe median, and validate it empirically using data from two online socialnetworks. Specifically, we show that for any user the majority of user'sfriends and followers have more friends, followers, etc. than the user, andthat this cannot be explained by statistical properties of sampling. Next, weexplore the behavioral origins of the paradoxes by using the shuffle test toremove correlations between node degrees and attributes. We find that paradoxesfor the mean persist in the shuffled network, but not for the median. Wedemonstrate that strong paradoxes arise due to the assortativity of userattributes, including degree, and correlation between degree and attribute.

Network Weirdness: Exploring the Origins of Network Paradoxes