Individual-Trait-Based Assortative Mixing in a Large Scientific Collaboration Network

Understanding the underlying mechanism of collaborative network formation is highly relying on the property of assortative/disassortative mixing patterns. Recent studies have shown that both of assortative and disassortative mixing patterns are widely existing in many social networks. However, it's not always been well-confirmed that people tend to connect with someone who has similar or dissimilar individual traits. In this study, we build a scientific collaboration network by the common publishing relationship with the APS journal papers and measure the scholars' degree assortativity and research interest assortativity. Our study has shown that the extent of assortative mixing behaviors of scholars may diversify from the different physics fields, or the social ties. In addition, the middle-level degree scholars play a vital role in bridging the collaborative communities and research fields, while this large group of members have not received adequate attention in the study of the science of science.

This work is supported by the NNSFC under Grant Nos. 71871042 and 71371040.