Problems with classification, hypothesis testing, and estimator convergence in the analysis of degree distributions in networks


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In their recent work Scale-free networks are rare, Broido and Clauset address the problem of the analysis of degree distributions in networks to classify them as scale-free at different strengths of scale-freeness. Over the last two decades, a multitude of papers in network science have reported that the degree distributions in many real-world networks follow power laws. Such networks were then referred to as scale-free. However, due to a lack of a precise definition, the term has evolved to mean a range of different things, leading to confusion and contradictory claims regarding scale-freeness of a given network. Recognizing this problem, the authors of Scale-free networks are rare try to fix it. They attempt to develop a versatile and statistically principled approach to remove this scale-free ambiguity accumulated in network science literature. Although their paper presents a fair attempt to address this fundamental problem, we must bring attention to some important issues in it.

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