APPRAISING DISCREPANCIES AND SIMILARITIES IN SEMANTIC NETWORKS USING CONCEPT-CENTERED SUBNETWORKS
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Date
2021-09-03
Authors
Medeuov, Darkhan
Roth, Camille
Puzyreva, Kseniia
Basov, Nikita
Journal Title
Journal ISSN
Volume Title
Publisher
Applied Network Science
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.
Description
Keywords
Type of access: Open Access, Semantic networks, Flood management, Computational text analysis
Citation
Medeuov, D., Roth, C., Puzyreva, K., & Basov, N. (2021). Appraising discrepancies and similarities in semantic networks using concept-centered subnetworks. Applied Network Science, 6(1). https://doi.org/10.1007/s41109-021-00408-0