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A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies

Social Network Analysis (SNA) is a set of techniques developed in the field of social and behavioral sciences research, in order to characterize and study the social relationships that are established among a set of individuals. When building a social network for performing an SNA analysis, an initi...

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Autores principales: Benítez-Andrades, José Alberto, Rodríguez-González, Alejandro, Benavides, Carmen, Sánchez-Valdeón, Leticia, García, Isaías
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266191/
https://www.ncbi.nlm.nih.gov/pubmed/30384476
http://dx.doi.org/10.3390/ijerph15112420
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author Benítez-Andrades, José Alberto
Rodríguez-González, Alejandro
Benavides, Carmen
Sánchez-Valdeón, Leticia
García, Isaías
author_facet Benítez-Andrades, José Alberto
Rodríguez-González, Alejandro
Benavides, Carmen
Sánchez-Valdeón, Leticia
García, Isaías
author_sort Benítez-Andrades, José Alberto
collection PubMed
description Social Network Analysis (SNA) is a set of techniques developed in the field of social and behavioral sciences research, in order to characterize and study the social relationships that are established among a set of individuals. When building a social network for performing an SNA analysis, an initial process of data gathering is achieved in order to extract the characteristics of the individuals and their relationships. This is usually done by completing a questionnaire containing different types of questions that will be later used to obtain the SNA measures needed to perform the study. There are, then, a great number of different possible network-generating questions and also many possibilities for mapping the responses to the corresponding characteristics and relationships. Many variations may be introduced into these questions (the way they are posed, the weights given to each of the responses, etc.) that may have an effect on the resulting networks. All these different variations are difficult to achieve manually, because the process is time-consuming and error-prone. The tool described in this paper uses semantic knowledge representation techniques in order to facilitate this kind of sensitivity studies. The base of the tool is a conceptual structure, called “ontology” that is able to represent the different concepts and their definitions. The tool is compared to other similar ones, and the advantages of the approach are highlighted, giving some particular examples from an ongoing SNA study about alcohol consumption habits in adolescents.
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spelling pubmed-62661912018-12-15 A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies Benítez-Andrades, José Alberto Rodríguez-González, Alejandro Benavides, Carmen Sánchez-Valdeón, Leticia García, Isaías Int J Environ Res Public Health Article Social Network Analysis (SNA) is a set of techniques developed in the field of social and behavioral sciences research, in order to characterize and study the social relationships that are established among a set of individuals. When building a social network for performing an SNA analysis, an initial process of data gathering is achieved in order to extract the characteristics of the individuals and their relationships. This is usually done by completing a questionnaire containing different types of questions that will be later used to obtain the SNA measures needed to perform the study. There are, then, a great number of different possible network-generating questions and also many possibilities for mapping the responses to the corresponding characteristics and relationships. Many variations may be introduced into these questions (the way they are posed, the weights given to each of the responses, etc.) that may have an effect on the resulting networks. All these different variations are difficult to achieve manually, because the process is time-consuming and error-prone. The tool described in this paper uses semantic knowledge representation techniques in order to facilitate this kind of sensitivity studies. The base of the tool is a conceptual structure, called “ontology” that is able to represent the different concepts and their definitions. The tool is compared to other similar ones, and the advantages of the approach are highlighted, giving some particular examples from an ongoing SNA study about alcohol consumption habits in adolescents. MDPI 2018-10-31 2018-11 /pmc/articles/PMC6266191/ /pubmed/30384476 http://dx.doi.org/10.3390/ijerph15112420 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Benítez-Andrades, José Alberto
Rodríguez-González, Alejandro
Benavides, Carmen
Sánchez-Valdeón, Leticia
García, Isaías
A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies
title A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies
title_full A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies
title_fullStr A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies
title_full_unstemmed A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies
title_short A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies
title_sort semantic social network analysis tool for sensitivity analysis and what-if scenario testing in alcohol consumption studies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266191/
https://www.ncbi.nlm.nih.gov/pubmed/30384476
http://dx.doi.org/10.3390/ijerph15112420
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