A 30-year bibliometric assessment and visualisation of emotion regulation research: applying network analysis and cluster analysis
| Date | 21 April 2023 |
| Pages | 85-100 |
| DOI | https://doi.org/10.1108/IDD-11-2022-0110 |
| Published date | 21 April 2023 |
| Subject Matter | Library & information science,Library & information services,Lending,Document delivery,Collection building & management,Stock revision,Consortia |
| Author | Samsur Rahaman,Punita Govil,Daud Khan,Tanja D. Jevremov |
A 30-year bibliometric assessment and
visualisation of emotion regulation research:
applying network analysis and cluster analysis
Samsur Rahaman and Punita Govil
Department of Education, Aligarh Muslim University, Aligarh, India
Daud Khan
Maulana Azad Library, Aligarh Muslim University, Aligarh, India, and
Tanja D. Jevremov
Faculty of Philosophy, University of Novi Sad, Novi Sad, Serbia
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 stud y 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 keywor d 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 conne ctivity, neuroimaging,
mindfulness, self-regulation, resilience and coping. The thematic evolution reflects that the research on emotion regulation has r ecently 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 regul ation
research.
Keywords Emotion regulation, Bibliometric analysis, Cluster analysis, Network analysis, Research trends, Thematic evolution
Paper type General review
Introduction
The field of developmental psychology is the one that
pioneered the concept of emotion regulation (McRae and
Gross, 2020). Fern
andez-Álvarez et al. (2018)defined emotion
regulation as “the processes deployed by an individual or group
of individuals to explicitly or implicitly influence the experienced
emotions in order to achieve desirable states or goals”.
Nowadays, emotion regulation is considered as one of the
fastest-growing fields of psychology (Gross, 2015;Tamir, 2011),
as evidenced by earlier research works on psychological stress,
coping (Lazarus,1966), cognitive (Miu and Crisan, 2011),
behavioural approach (Bargh and Williams, 2007), clinical
(Webb et al., 2012); developmental (Thompson, 2014),
biological (Hartley and Phelps, 2010), social (Schmader et al.,
2008), personality (Mayer and Salovey, 1995) and health
(DeSteno et al., 2013).
The past three decades have witnessed an unprecedented
growth in emotion regulation research (Moore et al.,2022;
Fern
andez-Álvarez et al., 2018). This proliferation of research
has rendered the field of emotion regulationas one of the most
intellectually stimulating and dynamic areas in the realm of
psychology. Conspicuously, as the volume of emotion
regulation research continues to expand, it becomes
increasingly important to synthesize and integrate the plethora
of findings and insights to inform the direction of future
research. Furthermore,the multidisciplinary nature of emotion
The current issue and full text archiveof this journal is available on Emerald
Insight at: https://www.emerald.com/insight/2398-6247.htm
Information Discovery and Delivery
52/1 (2024) 85–100
© Emerald Publishing Limited [ISSN 2398-6247]
[DOI 10.1108/IDD-11-2022-0110]
Received 2 November 2022
Revised 30 January 2023
Accepted 5 March 2023
85
regulation research, which spans the domains of clinical,
personality, social, developmental psychology as well as
cognitive and affective neurosciences and psychophysiology
(McRae and Gross, 2020;Gross, 2015), only further
accentuates the need to measure, monitor, assess and
comprehend the field of emotion regulation. In this regard,
bibliometric analysis can play a pivotal role in providing
valuable insights into the current state of emotion regulation
research.
Bibliometric analysis is a rigorous method for delving into
and deciphering vast amounts of scientificknowledge. It allows
us to disclose the evolutionarynuances of a particular discipline
and identify research trends, hotspots and areas that require
further exploration (Donthu et al., 2021). Recently, many
scholars (Dong et al.,2022;Guo et al.,2022;Lin et al.,2022;
Fei et al., 2022;Nie et al.,2022;Rong et al., 2022;Wu et al.,
2022;Yang et al., 2022;Wang et al., 2021;Yeung, 2018)
investigated various sub-disciplines of psychology through
bibliometric techniques to assess research performance,
uncover emerging research trends and themes, identify
research gaps and trace the evolution and development of
knowledge withinthe fields.
In this direction, the literature review indicates that Ribero
et al. (2013) and Fern
andez-Álvarez et al. (2018) examined
emotion regulation from the lens of bibliometric techniques.
However, both the studies ignored an in-depth keyword
analysis, citation analysis, cluster analysis and thematic
analysis, which are essential to identify research trends,
emerging research themes, research hotspots, and research
gaps, as well as for tracing the structure, evolution and
development of knowledge in the field of emotion regulation.
Given these limitations, it may be reported that these studies
could not capture a comprehensive picture of emotion
regulation research. To fill this research gap, we decided to
conduct a bibliometric study in the field of emotionregulation.
The present study:
analysed the impact and productivity of authors, journals,
institutions, and countries engaged in emotion regulation
research;
disclosed the highly cited studies (seminal work) in the
field of emotion regulation;
examined the structure and dynamics of international
scientific collaboration in emotion regulation research;
discovered the research hotspots, research trends and
research gap in the field of emotion regulation; and
explored the evolution and development of emotion
regulation field in the last 30 years, i.e. 1992–2021. This
study offers scholars and practitioners a new perspective
and suggestions for future challenges and policy
formulation.
Literature review and identification of research
gap
In bibliometric research, mathematical and statistical
methods are combined to produce in-depth information in a
particular field of study using different scientificdatabases and
software. The bibliometric analysis contributes to categorising
and evaluating bibliographic content by creating accurate
summaries of existing literature (Donthu et al.,2020).
Recently, bibliometric techniques have been employed in
various branches of knowledge to measure the output and
influence of scientific publications. The results gleaned by
bibliometric analysis are highly significant and assist
researchers in comparing different academic disciplines,
authors, institutions, geographic regions and even specific
countries (Siddique et al.,2023). Bibliometric techniques play
an essential role in identifying areas that require improvement
and highlighting the areas of strength in a given field of study.
Bibliometrictechniques also assist policymakers in determining
their desired future paths and in formulating policies (Adabre
et al.,2021;Gaggero et al., 2020). Over the past few years,
many researchers have investigated various subfields of
psychology by employing bibliometric and visualisation
techniques.A review of such studiesis presented here.
Rong et al. (2022) performed a bibliometric analysis in the
field of autism spectrumdisorder. A total of 40,597 papers were
published between 1998and 2021 and were extracted from the
Web of Science (WoS) database. The study quantitatively
analysed and visualised the network of authors, institutions,
nations and keywords related to autism spectrum disorder
research. Similarly, Yang et al. (2022) examined the literature
related to gut microbiota and schizophrenia research through
bibliometric analysis. This study analysed 162 publications
indexed in the WoS Core Collection and found that the gut–
brain axis and microbial-based therapies for schizophrenia are
key research hotspots involving schizophrenia and the gut
microbiota. Wu et al. (2022) conducted a bibliometric analysis
of dyslexia research published from 2000 to 2021. A total of
9,166 documents related to dyslexia were extracted from the
Social Sciences Citation Index and Science Citation Index
Expanded. The gathered data was analysed and evaluated
based on factors like the co-occurrence of nation, institution,
author and author keywords using Derwent Data Analyzer
software. In another study, Wu et al. (2020) investigated the
intimate partner violence research field using bibliometric
techniques. Furthermore,a bibliometric study on delirium was
carried out by Fei et al. (2022), which evaluated the 100 most-
cited articles on delirium sourced from the WoS database. Lin
et al. (2022) examined the research on cognitive behavioural
therapy for cancer with data sourced from WoS during the
period from 2012 to 2022 using different software such as
Biblioshiny, VOSviewer and CiteSpace. Nie et al. (2022) used
bibliometric techniques to investigate epigenetic research on
childhood trauma during 2000–2021 with data gathered from
the WoS Core Collection. The study found rapid growth in
publications after 2010; however, a lack of international
scientific collaboration was also observed. Furthermore, a co-
occurrence analysis was conducted by Cai et al. (2022)
regarding the connection between electroconvulsive therapy
and depressive disorderresearch from 2012 to 2021. The study
found that electroconvulsive therapy, treatment-resistant
depression, bipolar disorder, hippocampus, efficacy and
electrode location are key research hotspots. Several studies
have also investigated other areas of psychology using
bibliometric techniques; for example, Wang et al. (2021)
conducted a bibliometric analysis on mindfulness and
meditation research; Plusquellec and Denault (2018)
examined 1,000 highly cited works related to visiblenonverbal
behaviour; Yeung (2018) analysed the functional magnetic
Bibliometric assessment
Samsur Rahaman et al.
Information Discovery and Delivery
Volume 52 · Number 1 · 2024 · 85–100
86
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