One of the essential problems in bibliometrics is to understand patterns of interaction between authors. The traditional analysis of co-authorship networks can provide an useful insight into the structures of scientific disciplines, but its capability is limited since the analysis only takes into account direct connections between scientists. In this paper, we propose a new method for creation of author proximity networks that enhances the traditional bibliometric coupling network approach. We propose a new metric that calculates the proximity between two authors based on the number of common authors they cite. This metric includes both direct co-authorship and more complex, indirect citation connections. Using a SCOPUS dataset we constructed both a co-authorship network and an author proximity network based on the new metric. The results showed that both networks are scale-free and their degree distributions follow a power law. Moreover, we conducted a cross-country proximity analysis, grouping authors from the same country into one group.