We explore the structure of meanings in human language through the
analysis of colexification networks, developing methods to automatically
improve affective science resources. We prove that affective meaning is
encoded in colexification networks and deploy such networks to improve
state of the art methods to infer the affective ratings of words. This
constitutes a first step towards explaina...