The friendship paradox is the observation that friends of individuals tend to have more friends or be more popular than the individuals themselves. In this work, we first study local metrics to capture the strength of the paradox and the direction of the paradox from the perspective of individual nodes, i.e., an indication of whether the individual is more or less popular than its friends. These local metrics are aggregated, and global metrics are proposed to express the phenomenon on a network-wide level. Theoretical results show that the defined metrics are well-behaved enough to capture the friendship paradox. We also theoretically analyze the behavior of the friendship paradox for popular network models in order to understand regimes where friendship paradox occurs. These theoretical findings are complemented by experimental results on both network models and real-world networks. By conducting a correlation study between the proposed metrics and degree assortativity, we experimentally demonstrate that the phenomenon of the friendship paradox is related to the well-known phenomenon of assortative mixing.
Pal, S., Yu, F., Novick, Y., Swami, A., & Bar-Noy, A. (2019). A study on the friendship paradox – quantitative analysis and relationship with assortative mixing. Applied Network Science, 4 (71), 1-26. https://doi.org/10.1007/s41109-019-0190-8
The original material can be found here: https://doi.org/10.1007/s41109-019-0190-8
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