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Appraising discrepancies and similarities in semantic networks using concept-centered subnetworks. / Medeuov, Darkhan; Roth, Camille; Puzyreva, Kseniia ; Basov , Nikita .

в: Applied Network Science, Том 6, № 1, 66, 03.09.2021.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

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Medeuov, Darkhan ; Roth, Camille ; Puzyreva, Kseniia ; Basov , Nikita . / Appraising discrepancies and similarities in semantic networks using concept-centered subnetworks. в: Applied Network Science. 2021 ; Том 6, № 1.

BibTeX

@article{d4206ff2c155442d8b7320912ee35f3b,
title = "Appraising discrepancies and similarities in semantic networks using concept-centered subnetworks",
abstract = "This article proposes an approach to compare semantic networks using concept-centered sub-networks. A concept-centered sub-network is defined 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 flood management practice in England.",
keywords = "Semantic networks, Flood management, Computational text analysis, FLOOD RISK-MANAGEMENT",
author = "Darkhan Medeuov and Camille Roth and Kseniia Puzyreva and Nikita Basov",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = sep,
day = "3",
doi = "10.1007/s41109-021-00408-0",
language = "English",
volume = "6",
journal = "Applied Network Science",
issn = "2364-8228",
publisher = "Springer Nature",
number = "1",

}

RIS

TY - JOUR

T1 - Appraising discrepancies and similarities in semantic networks using concept-centered subnetworks

AU - Medeuov, Darkhan

AU - Roth, Camille

AU - Puzyreva, Kseniia

AU - Basov , Nikita

N1 - Publisher Copyright: © 2021, The Author(s).

PY - 2021/9/3

Y1 - 2021/9/3

N2 - This article proposes an approach to compare semantic networks using concept-centered sub-networks. A concept-centered sub-network is defined 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 flood management practice in England.

AB - This article proposes an approach to compare semantic networks using concept-centered sub-networks. A concept-centered sub-network is defined 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 flood management practice in England.

KW - Semantic networks

KW - Flood management

KW - Computational text analysis

KW - FLOOD RISK-MANAGEMENT

UR - https://appliednetsci.springeropen.com/articles/10.1007/s41109-021-00408-0

UR - http://www.scopus.com/inward/record.url?scp=85114383108&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/c9338b5a-65b3-362b-a482-2a809d58fa06/

U2 - 10.1007/s41109-021-00408-0

DO - 10.1007/s41109-021-00408-0

M3 - Article

VL - 6

JO - Applied Network Science

JF - Applied Network Science

SN - 2364-8228

IS - 1

M1 - 66

ER -

ID: 85572972