Natural Language Use as Bipartite Networks in Psychology

Abstract

Natural language as a data source is quite common in different divisions of psychology. Among the several ways to analyze the information conveyed by natural language, psychologists rarely use bipartite networks despite the strong potential that this network perspective has for enriching psychology's research toolbox. This opinion article aims to provide a viewpoint on current advances and promising future research directions on modeling natural language as a bipartite network structure, using word-of-mouth as the basis for a tutorial exposition that paves the way for others to leverage the opportunities provided by network theory.