Quantifying external information in social network analysis: an application to comparative mythology
Fecha
2023Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión aceptada / Onetsi den bertsioa
Identificador del proyecto
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-119478GB-I00/ES/
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-122916NB-I00
Impacto
|
10.1109/TCYB.2023.3239555
Resumen
Social network analysis is a popular tool to understand the relationships between interacting agents by studying the structural properties of their connections. However, this kind of analysis can miss some of the domain-specific knowledge available in the original information domain and its propagation through the associated network. In this work, we develop an extension of classical social netwo ...
[++]
Social network analysis is a popular tool to understand the relationships between interacting agents by studying the structural properties of their connections. However, this kind of analysis can miss some of the domain-specific knowledge available in the original information domain and its propagation through the associated network. In this work, we develop an extension of classical social network analysis to incorporate external information from the original source of the network. With this extension we propose a new centrality measure, the semantic value, and a new affinity function, the semantic affinity, that establishes fuzzy-like relationships between the different actors in the network. We also propose a new heuristic algorithm based on the shortest capacity problem to compute this new function. As an illustrative case study, we use the novel proposals to analyze and compare the gods and heroes from three different classical mythologies: 1) Greek; 2) Celtic; and 3) Nordic. We study the relationships of each individual mythology and those of the common structure that is formed when we fuse the three of them. We also compare our results with those obtained using other existing centrality measures and embedding approaches. In addition, we test the proposed measures on a classical social network, the Reuters terror news network, as well as in a Twitter network related to the COVID-19 pandemic. We found that the novel method obtains more meaningful comparisons and results than previous existing approaches in every case. [--]
Materias
Centrality measuress,
Comparative mythology,
Electronic mail,
Heuristic algorithms,
Mythology,
Network analyzers,
Network architecture,
Semantic value,
Semantics,
Social network analysis,
Social networking (online),
Standards,
Word embeddings
Editor
IEEE
Publicado en
IEEE Transactions on Cybernetics, 1-10
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Versión del editor
Entidades Financiadoras
The work of Javier Fumanal-Idocin and Humberto
Bustince was supported by the Project PID2019-108392GB I00 under Grant
AEI/10.13039/501100011033. The work of Oscar Cordón was supported by
the Government of Spain under Grant MCIN/AEI/10.13039/501100011033/
and CONFIA under Grant PID2021-122916NB-I00, including European
Regional Development Funds (ERDF) “FEDER, Una manera de hacer
Europa.” The work of Antonio-Francisco Roldán López-de-Hierro was
supported in part by the Project PID2020-119478GB-I00 and in part
by the FEDER Project under Grant A-FQM-170-UGR20
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