Resilience and social change: Findings from research trends using association rule mining
This study analyzed the historical development of resilience with respect to multidisciplinary aspects using association rule mining (ARM). ARM is a rule-based machine-learning approach tailored to identify validated relations among multiple variables in a large dataset. This study collected author...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Elsevier
2023-08-01
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Series: | Heliyon |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023059741 |
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author | Cheongil Kim Jaesun Yeom Seunghoo Jeong Ji-Bum Chung |
author_facet | Cheongil Kim Jaesun Yeom Seunghoo Jeong Ji-Bum Chung |
author_sort | Cheongil Kim |
collection | DOAJ |
description | This study analyzed the historical development of resilience with respect to multidisciplinary aspects using association rule mining (ARM). ARM is a rule-based machine-learning approach tailored to identify validated relations among multiple variables in a large dataset. This study collected author keywords from all resilience-related literature in the Web of Science database and examined the changes in validated resilience-related topics using ARM. We found that resilience-related research tends to diversify and expand over time. Although topics and their academic fields related to engineering and complex adaptive systems were prominent in the early 2000s, psychosocial resilience and social-ecological resilience have received significant attention in recent years. The increasing interest in resilience-related topics linked to psychological and ecological factors, as well as social system components, can be attributed to the impact of a series of complex and global events that occurred in the late 2000s. Recently, resilience has been conceived as a way of thinking, perspective, or paradigm to address emergent complexity and uncertainty with vague concepts. Resilience is increasingly being regarded as a boundary spanner that promotes communication and collaboration among stakeholders who share different interests and scientific knowledge. |
first_indexed | 2024-03-12T12:21:58Z |
format | Article |
id | doaj.art-c52aec4f14694eb6893bfbc3910abc15 |
institution | Directory Open Access Journal |
issn | 2405-8440 |
language | English |
last_indexed | 2024-03-12T12:21:58Z |
publishDate | 2023-08-01 |
publisher | Elsevier |
record_format | Article |
series | Heliyon |
spelling | doaj.art-c52aec4f14694eb6893bfbc3910abc152023-08-30T05:52:31ZengElsevierHeliyon2405-84402023-08-0198e18766Resilience and social change: Findings from research trends using association rule miningCheongil Kim0Jaesun Yeom1Seunghoo Jeong2Ji-Bum Chung3School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of KoreaSchool of Business Administration, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of KoreaAdvanced Railroad Civil Engineering Division, Korea Railroad Research Institute (KRRI), Uiwang, 16105, Republic of Korea; Corresponding author.School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea; Corresponding author.This study analyzed the historical development of resilience with respect to multidisciplinary aspects using association rule mining (ARM). ARM is a rule-based machine-learning approach tailored to identify validated relations among multiple variables in a large dataset. This study collected author keywords from all resilience-related literature in the Web of Science database and examined the changes in validated resilience-related topics using ARM. We found that resilience-related research tends to diversify and expand over time. Although topics and their academic fields related to engineering and complex adaptive systems were prominent in the early 2000s, psychosocial resilience and social-ecological resilience have received significant attention in recent years. The increasing interest in resilience-related topics linked to psychological and ecological factors, as well as social system components, can be attributed to the impact of a series of complex and global events that occurred in the late 2000s. Recently, resilience has been conceived as a way of thinking, perspective, or paradigm to address emergent complexity and uncertainty with vague concepts. Resilience is increasingly being regarded as a boundary spanner that promotes communication and collaboration among stakeholders who share different interests and scientific knowledge.http://www.sciencedirect.com/science/article/pii/S2405844023059741ResilienceResilience thinkingSocial changeResearch trendsAssociation rule miningBibliometric analysis |
spellingShingle | Cheongil Kim Jaesun Yeom Seunghoo Jeong Ji-Bum Chung Resilience and social change: Findings from research trends using association rule mining Heliyon Resilience Resilience thinking Social change Research trends Association rule mining Bibliometric analysis |
title | Resilience and social change: Findings from research trends using association rule mining |
title_full | Resilience and social change: Findings from research trends using association rule mining |
title_fullStr | Resilience and social change: Findings from research trends using association rule mining |
title_full_unstemmed | Resilience and social change: Findings from research trends using association rule mining |
title_short | Resilience and social change: Findings from research trends using association rule mining |
title_sort | resilience and social change findings from research trends using association rule mining |
topic | Resilience Resilience thinking Social change Research trends Association rule mining Bibliometric analysis |
url | http://www.sciencedirect.com/science/article/pii/S2405844023059741 |
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