Bailey C. Benedict, Seungyoon Lee, Caitlyn M. Jarvis, Laura K. Siebeneck, Rachel Wolfe
{"title":"在灾难研究中利用定性数据进行社会网络分析:机遇、挑战和例证。","authors":"Bailey C. Benedict, Seungyoon Lee, Caitlyn M. Jarvis, Laura K. Siebeneck, Rachel Wolfe","doi":"10.1111/disa.12605","DOIUrl":null,"url":null,"abstract":"<p>An abundance of unstructured and loosely structured data on disasters exists and can be analysed using network methods. This paper overviews the use of qualitative data in quantitative social network analysis in disaster research. It discusses two types of networks, each with a relevant major topic in disaster research—that is, (i) whole network approaches to emergency management networks and (ii) personal network approaches to the social support of survivors—and four usable forms of qualitative data. This paper explains five opportunities afforded by these approaches, revolving around their flexibility and ability to account for complex network structures. Next, it presents an empirical illustration that extends the authors' previous work examining the sources and the types of support and barrier experienced by households during long-term recovery from Hurricane (Superstorm) Sandy (2012), wherein quantitative social network analysis was applied to two qualitative datasets. The paper discusses three challenges associated with these approaches, related to the samples, coding, and bias.</p>","PeriodicalId":48088,"journal":{"name":"Disasters","volume":"48 2","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/disa.12605","citationCount":"0","resultStr":"{\"title\":\"Utilising qualitative data for social network analysis in disaster research: opportunities, challenges, and an illustration\",\"authors\":\"Bailey C. Benedict, Seungyoon Lee, Caitlyn M. Jarvis, Laura K. Siebeneck, Rachel Wolfe\",\"doi\":\"10.1111/disa.12605\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>An abundance of unstructured and loosely structured data on disasters exists and can be analysed using network methods. This paper overviews the use of qualitative data in quantitative social network analysis in disaster research. It discusses two types of networks, each with a relevant major topic in disaster research—that is, (i) whole network approaches to emergency management networks and (ii) personal network approaches to the social support of survivors—and four usable forms of qualitative data. This paper explains five opportunities afforded by these approaches, revolving around their flexibility and ability to account for complex network structures. Next, it presents an empirical illustration that extends the authors' previous work examining the sources and the types of support and barrier experienced by households during long-term recovery from Hurricane (Superstorm) Sandy (2012), wherein quantitative social network analysis was applied to two qualitative datasets. The paper discusses three challenges associated with these approaches, related to the samples, coding, and bias.</p>\",\"PeriodicalId\":48088,\"journal\":{\"name\":\"Disasters\",\"volume\":\"48 2\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/disa.12605\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Disasters\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/disa.12605\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Disasters","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/disa.12605","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Utilising qualitative data for social network analysis in disaster research: opportunities, challenges, and an illustration
An abundance of unstructured and loosely structured data on disasters exists and can be analysed using network methods. This paper overviews the use of qualitative data in quantitative social network analysis in disaster research. It discusses two types of networks, each with a relevant major topic in disaster research—that is, (i) whole network approaches to emergency management networks and (ii) personal network approaches to the social support of survivors—and four usable forms of qualitative data. This paper explains five opportunities afforded by these approaches, revolving around their flexibility and ability to account for complex network structures. Next, it presents an empirical illustration that extends the authors' previous work examining the sources and the types of support and barrier experienced by households during long-term recovery from Hurricane (Superstorm) Sandy (2012), wherein quantitative social network analysis was applied to two qualitative datasets. The paper discusses three challenges associated with these approaches, related to the samples, coding, and bias.
期刊介绍:
Disasters is a major, peer-reviewed quarterly journal reporting on all aspects of disaster studies, policy and management. It provides a forum for academics, policymakers and practitioners to publish high-quality research and practice concerning natural catastrophes, anthropogenic disasters, complex political emergencies and protracted crises around the world. The journal promotes the interchange of ideas and experience, maintaining a balance between field reports, case study articles of general interest and academic papers. Disasters: Is the leading journal in the field of disasters, protracted crises and complex emergencies Influences disaster prevention, mitigation and response policies and practices Adopts a world-wide geographical perspective Contains a mix of academic papers and field studies Promotes the interchange of ideas between practitioners, policy-makers and academics.