定性数据的网络分析:一种用于可视化和评估参与者定性贡献相似性的集成软件应用

IF 3.8 1区社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY

Journal of Mixed Methods Research Pub Date : 2021-12-02 DOI:10.1177/15586898211051584

Manuel S. González Canché

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引用次数: 5

摘要

这篇评论是对Whatley和Stich(2021)文章的回应，他们在文章中提出了网络分析方法和定性编码数据的集成。该研究的主要作者参加了2019年美国教育研究协会(AERA)扩展专业发展研讨会，我在那里提供了这个框架，并参加了统计和社会网络分析应用研讨会，我在那里开发了这个框架，并于2013年开始提供。除了每年举办8年的研讨会和自2019年以来每年举办的AERA研讨会外，我还于2016年和2017年在加州大学洛杉矶分校举办了研讨会。至少有750人参加了这些研讨会和讲习班;此外，包含该综合框架的已发表手稿(Gonz´alez Canch´e, 2019)已被下载超过1300次。重要的是，这种综合框架的明显影响，研讨会和研讨会参与者多年来提供的积极反馈，以及用于实现这种混合方法研究框架(R项目)的免费编程代码软件，绝大多数研讨会参与者都无法在他们自己的研究中应用“定性数据的网络分析”(NAQD)。这些程序是大量的统计和计算机编程代码，需要先进的数据管理和矩阵操作技能，这两者都代表了NAQD在定性和混合方法研究中的主流应用的真正困难的障碍。事实上，尽管多年来一直向学生和研讨会参与者提供所有统计代码，但只有少数参与者能够超越这些显著的障碍。因此，这篇评论是基于这样一种观点，即时间必须消除这些障碍，以便提供有意义的途径

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Network Analysis of Qualitative Data: An Integrative Software Application to Visualize and Assess Similarities in Participants’ Qualitative Contributions

Content This commentary is in response to Whatley and Stich ’ s (2021) article in which they present an integration of network analyses methods and qualitatively coded data. The lead author of that study participated both in the 2019 American Educational Research Association (AERA) ex-tended professional development workshop where I offered this framework and in the applied seminar on statistical and social network analysis where I developed this framework and began offering it in 2013. In addition to offering this seminar annually for 8 years now and the AERA workshops annually since 2019, I also offered workshops at the University of California, Los Angeles, in 2016 and 2017. At least 750 people have participated in these seminars and workshops; additionally, the published manuscript containing this integrative framework (Gonz´alez Canch´e, 2019) has been downloaded over 1300 times. Importantly, the apparent reach of this integrative framework, the positive feedback offered by seminar and workshop participants throughout the years, and the cost-free programming code software used to implement this mixed method research framework (The R Project), the vast majority of workshop attendees have been unable to apply “ Network Analysis of Qualitative Data ” (NAQD) in their own research. These procedures are statistically and computer programming code heavy and require advanced data management and matrix manipulation skills, both of which represent truly dif ﬁ cult barriers for NAQD ’ s mainstream application to qualitative and mixed methods research. Indeed, though all statistical code has been consistently provided to students and workshop attendees throughout the years, only a handful of participants have been able to surpass these remarkable hurdles. This commentary is therefore founded on the idea that the time has to remove these barriers in order to offer meaningful access to the

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来源期刊

Journal of Mixed Methods Research SOCIAL SCIENCES, INTERDISCIPLINARY-

CiteScore

10.40

自引率

28.20%

发文量

期刊介绍： The Journal of Mixed Methods Research serves as a premiere outlet for ground-breaking and seminal work in the field of mixed methods research. Of primary importance will be building an international and multidisciplinary community of mixed methods researchers. The journal''s scope includes exploring a global terminology and nomenclature for mixed methods research, delineating where mixed methods research may be used most effectively, creating the paradigmatic and philosophical foundations for mixed methods research, illuminating design and procedure issues, and determining the logistics of conducting mixed methods research. JMMR invites articles from a wide variety of international perspectives, including academics and practitioners from psychology, sociology, education, evaluation, health sciences, geography, communication, management, family studies, marketing, social work, and other related disciplines across the social, behavioral, and human sciences.