A 30-year bibliometric assessment and visualisation of emotion regulation research: applying network analysis and cluster analysis

IF 2.1 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
Samsur Rahaman, Punita Govil, Daud Khan, Tanja Jevremov
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引用次数: 0

Abstract

Purpose The emotion regulation research has drawn considerable attention from academicians and scholars in the contemporary world. As a result, the publications that are specifically dedicated to emotion regulation research are rapidly escalating. Therefore, this study aims to conduct a bibliometric analysis of research articles that have been published in the field of “emotion regulation.” The study primarily examines the growth and development of scholarly publications, seminal studies, influential authors, productive journals, research production and collaboration among countries, emerging research themes, research hotspots and thematic evolution of emotion regulation research. Design/methodology/approach The Web of Science Core Collection database was used to gather the study’s data, which was then analysed using VOSviewer and Bibliometrix, Biblioshiney open-source package of the R language environment. Findings The study’s results reveal that the research on emotion regulation has grown significantly over the last three decades. Notably, Emotion and Frontiers in Psychology are the most dominant and productive journals in the field of emotion regulation research. The most prominent author in the area of emotion regulation is identified as James Gross, followed by Gratz, Wang and Tull. The USA is at the forefront of research on emotion regulation and has collaborated with most of the developed countries like Germany, England and Canada. The keyword analysis revealed that the most potential research areas in the field of emotion regulation are functional magnetic resonance imaging, amygdala, post-traumatic stress disorder, borderline personality disorder, alexithymia, emotion dysregulation, depression, anxiety, functional connectivity, neuroimaging, mindfulness, self-regulation, resilience and coping. The thematic evolution reflects that the research on emotion regulation has recently focused on issues including Covid-19, non-suicidal self-injury, psychological distress, intimate partner violence and mental health. Originality/value The results of this study highlighted the current knowledge gaps in emotion regulation research and suggested areas for further investigation. The present study could be useful for researchers, academicians, planners, publishers and universities engaged in emotion regulation research.
情绪调节研究的30年文献计量评估和可视化:应用网络分析和聚类分析
目的情绪调控研究已引起当代学术界的广泛关注。因此,专门用于情绪调节研究的出版物正在迅速增加。因此,本研究旨在对“情绪调节”领域发表的研究文章进行文献计量分析。本研究主要考察学术出版物、开创性研究、有影响力的作者、富有成效的期刊、研究成果和国家间合作、新兴研究主题、,情绪调控研究的研究热点和主题演变。设计/方法/方法使用Web of Science核心收藏数据库收集研究数据,然后使用VOSviewer和Bibliometrix(R语言环境的Biblioshiney开源包)对数据进行分析。研究结果表明,在过去的三十年里,对情绪调节的研究有了显著的发展。值得注意的是,《情绪》和《心理学前沿》是情绪调节研究领域最具影响力和成果的期刊。情绪调节领域最著名的作者是詹姆斯·格罗斯,其次是格拉茨、王和塔尔。美国处于情绪调节研究的前沿,并与德国、英国和加拿大等大多数发达国家合作。关键词分析显示,情绪调节领域最有潜力的研究领域是功能性磁共振成像、杏仁核、创伤后应激障碍、边缘型人格障碍、述情障碍、情绪失调、抑郁、焦虑、功能连接、神经成像、正念、自我调节、恢复力和应对。主题演变反映出,情绪调节的研究最近集中在新冠肺炎、非自杀性自我伤害、心理困扰、亲密伴侣暴力和心理健康等问题上。原创性/价值本研究的结果突出了当前情绪调节研究中的知识差距,并提出了进一步调查的领域。本研究对从事情绪调节研究的研究人员、学者、规划者、出版商和大学都有帮助。
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来源期刊
Information Discovery and Delivery
Information Discovery and Delivery INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
5.40
自引率
4.80%
发文量
21
期刊介绍: Information Discovery and Delivery covers information discovery and access for digital information researchers. This includes educators, knowledge professionals in education and cultural organisations, knowledge managers in media, health care and government, as well as librarians. The journal publishes research and practice which explores the digital information supply chain ie transport, flows, tracking, exchange and sharing, including within and between libraries. It is also interested in digital information capture, packaging and storage by ‘collectors’ of all kinds. Information is widely defined, including but not limited to: Records, Documents, Learning objects, Visual and sound files, Data and metadata and , User-generated content.
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