APPRAISING DISCREPANCIES AND SIMILARITIES IN SEMANTIC NETWORKS USING CONCEPT-CENTERED SUBNETWORKS

Abstract

This article proposes an approach to compare semantic networks using conceptcentered sub-networks. A concept-centered sub-network is defned as an induced network whose vertex set consists of the given concept (ego) and all its adjacent concepts (alters) and whose link set consists of all the links between the ego and alters (including alter-alter links). By looking at the vertex and link overlap indices of concept-centered networks we infer semantic similarity of the underlying concepts. We cross-evaluate the semantic similarity by close-reading textual contexts from which networks are derived. We illustrate the approach on written and interview texts from an ethnographic study of food management practice in England.