LAUSR

Researchers have applied multiple methods, like co‐authorship and author co‐citation, to measure the relationships between authors and author similarity. These methods play a critical role in various applications of informetrics. A more delicate approach to gauging author similarity improves the related applications. By applying the method developed by the multiplex network, this study investigated how to identify author similarity by the mesoscale structures of author topic networks, which represent an author's research topic by organizing the interactions of the topic terms of their publications. Compared with the co‐authorship relationship and topic‐term similarity results, identifying author similarity by the mesoscale structure of author topic networks provides a better result reflecting how close authors’ research topics are.