Bibliometric Analysis of the Scientific Research on Sustainability in the Impact of Social Media on Higher Education during the COVID-19 Pandemic

Abstract

The COVID-19 pandemic has created massive issues around the world. To ensure that education continued during the crisis, educational institutions had to implement a variety of initiatives. This paper aims to examine the growth and country collaboration on social media (SM) research during the COVID-19 pandemic through a systematic review and investigate the impact of this body of work by citation and network analyses. The number of articles, keywords, and clusters of worldwide academic scholars working in the area was mapped using R studio and the VOS viewer tool. According to the study results, 519 articles have been retrieved from the Web of Science in the field of domain. The USA has produced the most publications, and Chen IH and Lin CY were the most prolific authors. Furthermore, the most studies on SM use in higher education were released in the International Journal of Environmental Research and Public Health. This research will help academic researchers, organizations, and policymakers to understand the ongoing research on SM during the last pandemic. It will help future academics analyze the evolution of social media technologies in higher education throughout the pandemic and identify areas for further study.

1. Introduction

The recent pandemic of COVID-19 has significantly impacted higher education worldwide [1]. It has necessitated the adoption of novel strategies and complementary and integrative initiatives in higher education to ensure the continuity of education during this crisis. From a technical perspective, the use of emerging or streamlined technologies such as social media and web-conferencing platforms has raised important issues such as code of ethics, data regulation, privacy protection, and security [2].

The SM was widely used around the world and evolved into a platform for disseminating information to the general public during the COVID-19 outbreak [3]. People have accessed SM via laptops, mobile, tablets, and also other devices for authentic data exchange and social interaction. According to UNESCO, the use of SM has helped engage a large portion of the approximately 70 percent of the student population affected by the closure of educational institutions during the pandemic [4].

Various online tools were used during the COVID-19 lockdown, including live online classes via Skype; uploaded videos related to education via YouTube, Dacast, Panopto, Muvi, Hippo Video online video education, platforms; and live streams via Zype, etc. In this unprecedented crisis, higher education has explored the various exciting possibilities that new technologies bring to institutions, educators, and students [5]. Social media platforms including Google Plus, Instagram, Vimeo, Facebook, Pinterest, Twitter, Teacher Tube, and Flickr have been widely employed in classrooms to improve student interaction in learning [6].

The SM platforms can be used for a variety of reasons, including entertainment, social engagement, and professional networking [7]. The SM has many advantages, especially in instances such as the COVID-19 lockdown, but studies have also shown that it also has a negative side and that using it during a pandemic might have unfavorable repercussions [8].

The remaining article is organized as follows. By providing a summary of research that specifically addresses social media during COVID-19, we hope to promote knowledge exchange between nations and academic disciplines. Eight sections make up the rest of the paper. Section 2 explains the existing literature review on social media. Section 3 explains the objectives of social media research. Section 4 describes in detail the research methods employed for the study. Section 5 comprises seven subsections, with Section 5.1 discussing the global collaboration of documents, Section 5.2 describing document type distribution in social media research Section 5.3 identifying affiliations productivity, Section 5.4 examining author impact, Section 5.5 identifying cited manuscripts, Section 5.6 exploring journals leading in social media research, and Section 5.7 finding the core keyword of co-occurrence of author keywords. Finally, in Section 6, Section 7 and Section 8, the paper presents suggestions, conclusions, limitations, and the future scope of research.

2. Literature Review

The SM platform is a method for examining social systems by using social networking. Much research has been conducted in recent years employing social networking to examine topics associated with bibliometrics/scientometrics. For example, Zyoud et al. [9] examined the bibliometric traits of documents, such as publication growth, citation analysis, collaborative partnerships, as well as identification of frequently used phrases, for the papers’ role of SM in psychology. They searched for data to identify from the Web of Science and downloaded articles concerning social media in psychology published between 2004 and 2014. They found that the quantity of scientific papers on SM in the field of psychology had continuously increased over time. The USA had the highest h-index and accounted for 57.14% of all published articles. Furthermore, the majority of the documents were research articles (873), and most were written in English (99.06%).

Hosain [10] obtained 87 papers produced from 2010 to 2020 using the Web of Science. The author reviewed the contents of the papers and concluded that the majority of earlier research showed an increase in the use of SM data for various HRM practices. According to the author, LinkedIn and Facebook were indeed the most popular websites for recruiting workers. with Facebook primarily offering behavioral data and LinkedIn offering employment-related data. Finally, it was opined that companies could establish a powerful corporate brand by maintaining a presence in social media.

Gan and Wang [11] analyzed the output of the results of 3178 documents on social media research in China from WoS as a data source. The top three universities with the most publications were the Wuhan University, Renmin University of China, and Nanjing University. Additionally, the distribution of writers with various publications followed a power-law pattern, and the frequency of keywords followed a power-law distribution. The most important and frequently used keywords were social media, traditional media, the Internet, diffusion, and user.

Su et al. [12] thoroughly investigated the research output on social media analysis (SMA) over two decades at the international level. According to the findings, the USA is the most prolific with the most published social network analysis papers. “Computer Science” and “Business Economics” were the top two subject areas. Computers in Human Behavior was the leading publication for social network analysis articles. The scientific fields of “Social network analysis”, “Computer-mediated communication”, “Online learning”, “Social Network”, and “Community of inquiry” were found to be linked to social network analysis. Finally, the Kolmogorov–Smirnov (K-S) test demonstrated that Lotka’s rule was unquestionably obeyed by the frequency indices of the author output distribution.

Zhao et al. [13] investigated to compare SM and SN in marketing research published from 1996 to 2020. Their findings demonstrated the research hotspot status of social networks and social media within the field of marketing research. Social networks appeared to have more intricate intimacy nodes than social media. The keyword co-occurrence analysis further demonstrated that social networks’ study scope was broader than social media’s in marketing research.

Aparicio-Martinez et al. [14] conducted a bibliometric study using lists of documents in the health field related to SN and young people. The findings pointed to a vast body of study regarding SN, youth, and healthcare. The most prevalent publication type was a research article (68% of all publications), and the majority of the articles were detailed quantitative investigations (82%). Medicine was the most prevalent field in their paper, accounting for 6062 papers. As authors and contributors in international research collaborations, most scholars in the discipline were from North America.

The study quality and development trends in the field of event detection in social media were examined by Chen et al. [15]. The United States and the Republic of China were the most prominent, with the most contributions. It was found that the authors and affiliations frequently worked together and collaborated more when they were from the same region. Newly emerging subjects, such as the detection of Pharmacovigilance events, were among the 14 research themes identified by the researchers.

Given the scope and incidence of the worldwide pandemic, it is important to explore and empirically study its effects on higher education in particular, as well as education in general, to develop and implement the necessary strategies and plans focused on lessening its devastating effects. The existing literature on the effects of COVID-19 on education is still minimal because of the pandemic’s fast inception and spread, and it consists primarily of non-academic editorials or non-empirical personal observations, anecdotes, reports, and experiences (e.g., Baker; Chan) [16,17]). However, given this, the empirical study on the pandemic’s effects on higher education is fast expanding. For instance, Unger and Meiran [18] found that the pandemic caused US students to worry about performing digital learning assignments. Despite the increasing body of research, the studies only offer scant evidence on how the epidemic has affected online teaching and learning. For a deeper comprehension of the critical ramifications of the pandemic for higher education in online learning and teaching, further empirical research is required.

There are few pertinent systematic reviews in the area of SM research. The topic of social media event detection has seen several prominent tasks examined and summarized by Dong et al. [19]. In their article, Nurwidyantoro and Winarko [20] discussed many aspects of social media analysis for detecting various event categories, including news, traffic, outbreaks, and natural disasters. An overview of methods for event identification from Twitter streams was presented by Atefeh and Khreich [21].

Similar studies were found based on social media during the COVID-19 pandemic through systematic reviews; Korkmaz and Toraman [22] used data mining and analytic techniques of social network analysis and text-mining to perform a bibliometric analysis of the articles relating to COVID-19 and education to assess the pandemic’s effects. Rocha et al. [23] assessed the influence of social media on the spread of knowledge and its effects on health through a systematic review. The MedLine, Virtual Health Library (VHL), and Scielo databases were all thoroughly searched. Investigations that looked at how fake news affects patients and medical professionals globally were considered. Haddad et al. [24] revealed that during the COVID-19 pandemic, using social media excessively or problematically was associated with worse mental health outcomes, which may be prevented by employing logical thought, positivism, meditation, and cognitive restructuring.

This study encourages cross-disciplinary research that is based on the interdisciplinary study of social media and higher education. There has been a growing corpus of research concerning the widespread use of social media in recent publications. With this article, we hope to add a small bit to the body of knowledge on the usage of social media in higher education during the COVID-19 pandemic.

3. Objectives

The purpose of this study was to use bibliometric data analysis to assess the size and trends of the literature related to SM and higher education. The study’s major goals were to address the following question.

Q1. How has social media literature developed and changed over time?

Q2. What are the citation patterns using the VOS viewer tool on social media?

Q3. What are the trends and future directions for research on social media?

Bibliometric analysis is a data-driven method of examining a field of study and is increasingly used to map knowledge domains. Bibliometric analysis techniques are commonly used to indicate the scientific development of knowledge domains within a research field by analyzing the relationships between citations and co-authorships [25].

Bibliometric analyses were carried out to assess the research trends in the field of social media [26]. Several bibliometric/scientometric studies have looked at the patterns of SM use throughout the fields of psychology, medicine, and health care. However, a literature search has not yielded any bibliometric or scientometric study of SM and higher education during the recent pandemic [27]. As a result, the study was conducted to fill in the gaps by mapping the literature on the biggest and most well-known social media platforms and higher education (e.g., YouTube, TikTok, Facebook, Pinterest, Twitter, Snapchat, LinkedIn, and Instagram). This study covers terms of publications, citation analysis, countries cooperating, most prolific authors, and newly emerging publication topics related to the usage of SM and higher education during the last pandemic.

4. Methodology

This study used bibliographic data indexed in the Web of Science (WoS) database as the source for data. The WoS was chosen for data extraction because it includes articles from over 21,000 journals and sources and is the most widely used database for scientific publication analysis [28]. It also encompasses more research areas than Scopus, Google Scholar, and PubMed.

To maintain objectivity and transparency, the study followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach recommended, proposed by Moher et al. [29].

Authors from all over the world are utilizing the PRISMA statement 2015 when presenting the findings and creating the study framework. The systematic literature review (SLR) provides a roadmap for improving reviews and meta-analyses. Shahzad et al. [30] examined a meta-analysis of big data analytics with the perspective of fake news identification on electronic media., examined by Ansari and Farzadkia on beach debris quantity and composition [31] and explored by Royle et al. on citation rates and journal impact factors [32]. PRISMA is composed of four primary sections, each with different phases. Identifying is the initial step, which also includes creating focused research queries and a search plan. The second part is screening, which seeks to interpret and organize the data. The third phase is eligibility, which is carried out to assess the data using a planned, systematic assessment. Inclusion, the final step, is used to examine the data and create subsequent procedures. As seen in Figure 1, the PRISMA structure is comprised of the four processes of identification, screening, eligibility, and inclusion.

The Boolean and filtering functions were used to expand the scope of the keyword search to include information on social media in higher education during COVID-19 domains.: TOPIC: (“TS = social media AND TS = COVID AND TS = higher education”). The literature search’s timespan covered the last three years between 2019 and 2021. The keywords were chosen using data from earlier investigations. For instance, some researchers searched the literature using the terms “coronavirus” and “COVID-19” [33], while others used the terms “Social media”, “COVID-19”, “coronavirus”, and “COVID” [34]. The WoS was scanned for documents on social media using the twenty-two most common keywords in a study [35].

The search was conducted on 17 April 2022. At first, a total of 752 documents were displayed; however, this included all different kinds of documents, such as research articles, reviews, books, book chapters, etc. The data were extracted from the WoS in plain text format. We limited our literature search to the English language, all countries, research articles, and review papers, and 232 articles were excluded at this stage. This was implemented by carefully examining the literature’s titles and abstracts. The whole article was examined separately, and a decision was made regarding whether to include it if the abstracts and titles during COVID-19 research failed to discriminate between pertinent and irrelevant analyses related to SM and higher education. Thus, a total of 524 publications were now eligible for additional assessment and application of the eligible studies. The meta-analysis was then continued when the data were exported to an Excel sheet. Additionally, we eliminated five duplicate papers from the Excel sheet. The screening of publications based on the inclusion criteria produced 519 related articles after reading the abstracts. Figure 1 depicts the PRISMA framework implementation utilized for bibliometric analysis.

The collected data were evaluated and presented based on the following criteria: document type, authors, sources, affiliations, country/territory, collaboration, h-index, impact factor, and citations. The data were further examined to determine the connection between nations, organizations, and terms by showing the main clusters in each category using the VOS viewer program. The terms’ co-occurrence rates in clusters linked to the main theme were used to produce the map. MS Excel [36], R studio [37], and VOS viewer [38] software were used for the graphics.

Furthermore, we used VOS viewer software’s co-authorship analysis (countries and affiliations) and analysis of the co-occurrence of author keywords to show possible fields with minimum investigation. Finally, we utilized graphs produced by the Microsoft Excel 365 web application to present the primary data (document types, countries, and affiliations).

5. Results

5.1. Global Collaboration of Documents

Table 1. Global collaboration of documents on social media research.

Name of Country	Papers	Citations	Links	Total Link Strength
USA	377	821	1177	173
China	332	1316	1139	132
UK	127	128	300	124
India	108	225	466	69
Spain	83	322	374	80
Italy	77	156	191	78
Saudi Arabia	66	274	368	38
Australia	62	177	398	88
Poland	61	165	191	54
Pakistan	55	42	167	77

shows the productivity rating of the top ten countries based on the quantity of documents from the Web of Science dataset. In this list, the top four countries were from Asia (China, India, Saudi Arabia, and Pakistan). Furthermore, there were four countries (the UK, Spain, Italy, and Poland) from Europe, the USA from North America, and Australia from Oceania. The result shows that the United States was ranked first among the ten leading countries with 377 publications, followed by the second top-ranked country, China with 332, the UK with 127, and India with 108 papers. Remarkably, China (1316) and the USA (821) had the highest number of citations.

A network of 50 out of 106 countries presented a minimum of three documents, whereas a country with at least five citations in three clusters was to be considered; only 47 countries met the set threshold and were visually mapped using the VOS viewer, as shown in Figure 2. The co-authorship analysis of countries reveals the type and degree of collaboration in this subject as well as the relationship between the countries involved. Different colors are used to represent each cluster. The number of collaborations between the two nations is represented by the thickness of the link, while the size of the node symbolizes the number of publications emanating from that country [39].

Additionally, this visualization demonstrates the effectiveness of international cooperation. Regarding social media, the United States, China, England, and India are leading the way. In Figure 2, the red cluster shows the close collaboration between the USA, Australia, England, and other Asian countries (Saudi Arabia, Pakistan, Japan, and Taiwan). The red and green clusters are the ones with the most significant number of countries (27) and are led by the USA and the Netherlands. They are followed by the blue cluster, with 16 countries, including Switzerland, Spain, Italy, Germany, and Belgium, with Switzerland leading. The countries with the highest number of links were the USA with 377 documents and 1177 links, followed by China (413 links) and India (466 links). The USA was in the first position with total link strength of 173 followed by China (132 total link strengths), the UK (124 total link strengths), Australia (88 total link strengths), and Spain (80 total link strengths) (see Table 1).

5.2. Document Type Distribution in Social Media Research

The data on the distribution of research output by kind of publication document are shown in Figure 3. The study analyzed 519 articles. The most prominent type of document was an article (449, 86.51%), followed by early access (40), reviews (19), editorial materials (5), and reviews; early access (2). Furthermore, there was one each of book chapters (1), proceeding papers (1), corrections (1), and letters (1) type of documents.

5.3. Affiliation Productivity

Table 2. Affiliations productivity, links, and link strength in social media research.

Affiliations	Papers	Citations	Country	Affiliations	Links	TLS	Country
University of Gondar	14	84	Ethiopia	University of Melbourne	27	30	Australia
National Cheng Kung University	13	44	Taiwan	University of Cambridge	23	24	England
All India Institutes of Medical Sciences	12	49	India	University of Kent	21	22	England
Monash University	12	89	Hong Kong	University of Warwick	21	22	England
University of Hong Kong	12	28	Hong Kong	Education University of Hong Kong	20	20	Hong Kong
Charité Universitätsmedizin Berlin	11	26	Germany	University of Toronto	19	20	Canada
King Saud University	11	69	Saudi Arabia	University of Nevada	19	20	USA
Harvard Medical School	10	56	USA	Monash University	14	26	Australia
Hong Kong Polytechnic University	10	52	Hong Kong	Hong Kong Polytechnic University	7	20	Hong Kong
King Abdulaziz University	10	63	Saudi Arabia	National Cheng Kung University	6	19	Taiwan

TLS—Total Links Strength.

depicts a scientometric profile of the top 10 most productive affiliation institutes in social media publications. Approximately 1286 institutions were identified from the literature. It was found that a maximum of 14 and 13 publications were published by the University of Gondar and National Cheng Kung University, respectively. A minimum of 10 publications were published by the Harvard Medical School, Hong Kong Polytechnic University, and King Abdul-Aziz University. The results show that the top three institutions were in Hong Kong (Monash University, University of Hong, and Hong Kong Polytechnic University).

The closeness of the relationships is also indicated by the lines connecting each affiliation on the map. The stronger the link between the affiliations, the thicker the line [40]. The affiliation with the most publications, Monash University with the highest citation received, had the largest font on the map (see Figure 4). The productivity of affiliations and how they work together with other affiliations are depicted in the figure.

There were approximately 1286 organizations found, but we only looked at the ones that had published at least three research papers. The co-authorship affiliation was analyzed via VOS Viewer software. After applying the filter, 106 institutions were identified, and they were split into six clusters, each of which was represented by a distinct hue. The size of the nodes in the diagram corresponds to the amount of documents, and the strength of the edge in the figure corresponds to the level of collaboration.

Figure 4 provides a VOS viewer of visualization of the 50 most co-authorship affiliations, the threshold quantity of papers for affiliation was set at 3, and only 106 affiliations in six clusters matched the requirement. The size of the nodes in the diagram represents the quantity of documents, and the thickness of the edge in the figure represents the collaboration level [41]. The first cluster in red is the one with the most significant number of universities (18) and the University of Cambridge in the UK has the largest number of links (n-27 links), followed by the University of Kent (n-23) and the University of Warwick (n-21).

It is followed by the second cluster in green with 10 universities, including University College London, the University of Maryland, and Carolina University. The Minnan Normal University is included in the light blue cluster with seven universities. The University of Melbourne has the largest total link strength (n-30) among the six clusters, followed by Monash University (n-26) and the University of Cambridge with 24 TLS. This indicates that the most significant factor affecting collaborative relationships is not always a considerable advantage.

5.4. Author Impact

The data on the leading researchers/scholars were exported from the Web of Science database. The top 10 authors who were the most active on SM and higher education during the pandemic are included in

Table 3. Author impact on social media research.

Authors/Year	Papers	Citations	h-Index	g-Index	m-Index
Chen IH, 2021	5	44	4	5	2
Lin CY, 2021	5	44	4	5	2
Chen CY, 2021	4	42	4	4	2
Latner JD, 2021	3	36	3	3	1.5
Liu J, 2020	3	21	2	3	0.667
O’brien KSS, 2021	3	36	3	3	1.5
Rao TSS, 2020	3	103	3	3	1
Smith L, 2021	3	8	2	2	1
Abu Elnasr AE, 2020	2	48	2	2	0.667
Ahmad T, 2020	2	26	1	2	0.333

. The top two authors were from Hong Kong. Among the top ten authors, the most productive were Chen IH and Lin CY from the Hong Kong Polytechnic University with five papers each and Chen CY from Minnan Normal University in China with four papers. Rao TSS had the highest citations among these authors, with 103 citations. In addition to this, although ranked as the first and second leading authors, Chen IH, Lin CY, and Chen CY had the highest received h-index and g-index values. It can be seen that most of the authors were from Hong Kong, one of the most active countries in this research field.

5.5. Cited Manuscript

According to the quantity of citations that authors have obtained,

Table 4. Top ten cited manuscripts.

Name of Title	Citations	CPY	NC
Zhang, Y., and Ma, Z. F. (2020) [42]. Impact of the COVID-19 pandemic on mental health and quality of life among local residents in Liaoning Province, China: A cross-sectional study.	431	143.667	12.8762
Zhang et al., (2020) [43]. Survey of insomnia and related social psychological factors among medical staff involved in the 2019 novel coronavirus disease outbreak.	251	83.667	7.4987
Khubchandani et al., (2021) [44]. COVID-19 vaccination hesitancy in the United States: a rapid national assessment.	230	115	38.4144
Al-Mohaithef, M., and Padhi, B. K. (2020) [46]. Determinants of COVID-19 vaccine acceptance in Saudi Arabia: a web-based national survey.	186	62	5.5568
Celia et al., (2020) [47]. Changes in dietary behaviours during the COVID-19 outbreak confinement in the Spanish COVIDiet study.	178	59.333	5.3178
Ferdous et al., (2020) [48]. Knowledge, attitude, and practice regarding COVID-19 outbreak in Bangladesh: An online-based cross-sectional study.	115	38.333	3.4357
Peyrony, et al., (2020) [49]. Impact of panelists’ experience on script concordance test scores of medical students.	104	34.667	3.107
Habersaat et al., (2020) [50]. Ten considerations for effectively managing the COVID-19 transition.	103	34.333	3.0772
Georgiou et al., (2020) [51]. COVID-19-related conspiracy beliefs and their relationship with perceived stress and pre-existing conspiracy beliefs.	84	28	2.5095
Qi et al., (2020) [45]. The effect of social support on mental health in Chinese adolescents during the outbreak of COVID-19.	81	27	2.4199

CPY—Citations Per Year, NC—Normalized Citations.

presents the most frequently cited manuscript. The results show that eight manuscripts were cited at least 100 times. Two papers had fewer than 100 citations. “Impact of the COVID-19 pandemic on mental health and quality of life among residents in Liaoning Province, China: A cross-sectional study” by Zhang, Y. and Ma, Z. F. [42] had the highest number of citations received (431). “Survey of insomnia and related social psychological factors among medical staff involved in the 2019 novel coronavirus disease outbreak” by Zhang et al. [43] had the second-highest number of citations received. “COVID-19 vaccination hesitancy in the United States: a rapid national assessment” by Khubchandani et al. [44] had the third-highest number of citations received. The minimum number of citations was received by Qi et al. [45] for “The effect of social support on mental health in Chinese adolescents during the outbreak of COVID-19”, with only 81 citations.

5.6. Journals Leading in Social Media Research

Table 5. Top ten journals leading.

Sources	Papers	Citations	Quartile	Publishers
International Journal of Environmental Research and Public Health	42	674	2	MDPI
Sustainability	29	155	1	Springer
Journal of Medical Internet Research	23	227	1	JMIR
Frontiers in Psychology	22	80	2	Frontiers Media
Plos One	19	265	2	Public Library of Science
Frontiers in Public Health	13	37	2	Frontiers Media
Vaccines	12	141	2	MDPI
BMC Public Health	11	139	1	Springer
Frontiers in Psychiatry	8	313	1	Frontiers Media
Heliyon	8	67	1	Elsevier

highlights the bibliometric statistics for all documents published in 265 journals from 2019 to 2021. The International Journal of Environmental Research and Public Health was identified as the leading journal that has published the greatest quantity of papers (42), published by MDPI; followed by Sustainability with 29 papers, published by Springer; and the Journal of Medical Internet Research with 23 papers, published by JMIR. The International Journal of Environmental Research and Public Health and Frontiers in Psychiatry had the greatest number of citations, with 674 and 313 citations, respectively. One of the most important bibliometrics is a citation. It can assist future readers in choosing journals for publishing their work. Furthermore, the top ten journals were all from Quartiles 1 and 2, with no leading journals from Quartiles 3 and 4. This demonstrates that top-quality journals were publishing papers related to SM research.

5.7. Co-Occurrence of Author Keywords

Table 6. Co-occurrence of author keywords.

Keyword	Occurrences	Link Strengths
COVID 19	351	564
social media	79	231
pandemic	63	167
corona	57	145
mental health	33	84
vaccination	31	75
anxiety	28	84
depression	28	85
higher education	24	40
public health	24	70
knowledge	21	64
SARS-CoV-2	19	59
stress	19	50
attitudes	16	56
twitter	15	49
adolescents	13	23
infodemic	13	48
medical education	12	18
online learning	12	28
education	11	14

highlights the co-occurrence of author keywords for 3147 authors and 1258 indexed keywords by authors in the reviewed publications. It can be seen that the author keyword “COVID 19” has 351 occurrences (564 LS), followed by “social media” with 79 occurrences (351 LS), “pandemic” with 63 occurrences (1267 LS), “corona” with 57 occurrences (145 LS), and “mental health” with 33 occurrences (84 TLS).

We were able to determine the most popular terms and the relationships between them with the assistance of keyword analysis, which led us to the major research questions pertinent to the subject under study. The software was used to evaluate each term and calculate the links, overall link strengths, and co-occurrences of the keyword with other keywords [52].

To comprehend the core intellectual theme addressed by the existing study, a co-occurrence analysis using 3147 authors and 1258 indexed keywords was performed. “COVID 19” and “social media”, among the author keywords shown in Figure 5, appeared as prominent terms in the most interconnected platform, which can be addressed by looking at the interconnection links between keywords. The inclusion of keywords in this study was restricted to those that appeared at least three times. Table 6 displays the TLS for the top 20 keywords and index terms. The most frequently occurring keywords are represented by different nodes in Figure 5. These frequently used keywords are clustered differently in terms of node size, color, and font size and are linked together by lines based on their similarity [53]. The number of links between nodes reveals the frequency of those keywords occurring together, and the size of a node is inversely associated with the frequency of a term. The distance between two keywords decreases as the number of co-occurrences between them increases.

The lines of thickness indicate how strong the relationship between keywords is in comparison to the others. The strength of the relationship was determined by the fact that the keywords appeared together in the published articles, including the frequency.

Network visualization was also used to show how often the terms occurred together. As displayed in Figure 5, 1364 total links in the seven clusters were found during the analysis: in cluster 1 (n-10 occurrences), cluster 2 (n-10 occurrences), cluster 3 (n-8 occurrences), cluster 4 (n-7 occurrences), cluster 5 (n-6 occurrences), cluster 6 (n-5 occurrences), and cluster 7 (n-4 occurrences). In the previous studies, each group of keywords or concepts is represented by various colors using the VOS viewing tool, Cruz-Cárdenas et al. found five clusters [54], 7 clusters by Al-Zaman [55], and 5 clusters by Shamsi et al. [56]. Additionally, all cluster’s keywords were investigated to determine the cluster’s distinguishable theme based on the keywords’ corresponding distinguishable topics.

Cluster 1 (red) has “social media” as a major node in the center and combines other keywords such as “health communication,” and “youtube.” In light of the use of social networks during the COVID-19 pandemic, the cluster is, therefore, connected to SM. These could be considered hot topics in social media in higher education. An infodemic is an information overload during a disease outbreak that includes inaccurate or misleading information through physical and social media.

The phrase “COVID 19” is the center node of Cluster 2 (green). It brings together concepts such as “mental health”, “social distancing”, “stress”, “depression”, and “children.” Hence, this cluster regards the social distance between people, which affected more children and aged people during the COVID-19 pandemic.

The third largest cluster in dark blue, “vaccination”, is prominent in this cluster and groups together other keywords such as “communication” and “twitter”, etc. The COVID-19 vaccination is safe and continues to work well in avoiding fatalities, serious sicknesses, and hospitalizations.

In cluster 4 (yellow), “SARS-CoV-2” represented the closing of all educational institutions during the pandemic, through “video” and “information and communication technology” maintained learning system.

In cluster 5 (purple), the word “social media” is prominently represented by a node. We identified that social media platforms were widely used by institutions in developing nations to maintain e-learning and the educational process [35].

In the sixth cluster in blue, the keyword of “pandemic” was the link strength found among the top 50 author’s keywords. A pandemic is the global spread of a newly discovered illness. By examining the keywords associated with this cluster through the health information, respiratory viral illnesses with the highest chance of becoming a pandemic include those brought on by the novel influenza virus and COVID-19 [57].

Cluster 7 (orange), the smallest network cluster, with four keywords, including “attitudes”, “fear”, “knowledge”, and “practice” has no central node.

The research uncovered several groups of significant keywords that are related to one another in smaller groupings. Additionally, “COVID 19” is a core term that serves as a positioning system that is more closely related to other keywords such as “social media”, “pandemic”, and “corona.” In addition to “COVID 19”, “social media”, “pandemic”, and “corona” also frequently co-occur. This finding revealed a significant future study topic for SM-related medical research: the use of new technologies in medical services will grow in popularity and garner more scholarly interest.

6. Discussion

Social media has the massive advantages of accessibility and outreach for teaching and learning; cost and time savings, flexibility in location, cost savings in terms of travel, and increased inclusivity offered by social media are becoming increasingly comprehensive; however, it was not fully integrated into the educational system until the recent (COVID-19) pandemic struck the rest of the world [58].

This study uses publishing data from the WoS to provide a quantitative and qualitative description of the research on SM and higher education. To understand the current state of the research area based on publications and associated interactions, the study set out to undertake a systematic review that involved identifying important researchers, academic organizations, countries, hubs, progress, and emerging technologies. This study’s main goal was to map the research landscape of SM and higher education during the last pandemic, both in terms of quantity and content. To implement this, we used the following methods: co-authorship analysis, keyword co-occurrence analysis, spatial pattern research of publication quantity, and country collaboration of author, countries, and affiliations using the VOS viewer tool.

To analyze useful journals, the study results have highlighted that the maximum number of documents (42) with the highest citations were published in the International Journal of Environmental Research and Public Health. The University of Gondar from Ethiopia contributed the most publications (357), and with 377 and 332 publications each, the USA and China were the two most active leading countries. The findings of Cruz-Cárdenas et al. are supported by an analysis of the country collaboration map, which identified a large number of publications arising from cooperative research between different parts of the world [59]. Chen IH and Lin CY from the Hong Kong Polytechnic University were identified as the most prolific authors, with five papers each. The results indicate that based on the visualization map on affiliations, most institutions in the blue cluster are from Hong Kong, with Monash University in the lead. In the second-largest cluster in red, the University of Toronto led other institutions.

The research topic of articles is reflected in the keywords. We identified the co-occurrence of keywords, to look at research frontiers and hotspots in the field of SM and higher education during COVID-19. The core term “COVID 19” acts as a positioning system that connects to other keywords more closely, such as “social media”, “pandemic”, and “corona”. For the analysis of keywords, the keywords were observed as core sexually transmitted diseases and COVID-19. Sarirete reported the three most frequently used keywords including COVID-19, immunology, and virus vaccine [60]. Al-Zaman demonstrated the research trends on co-occurrence analysis of COVID-19 with keywords such as COVID-19, coronavirus, SARS-CoV-2, 2019-nCoV, and pneumonia [61]. Confente examined the main theoretical underpinning of social media in a business study of word-of-mouth [62]. Rashidi et al. illustrated that the six most popular co-occurrences were social media, Twitter, social networks, Facebook, data mining, and location-based social networks [63].

In addition to being utilized for professional and personal reasons, SM also provides new techniques and tools for the dissemination of information for several academic organizations [64,65]. In our study, we analyzed the communication and collaboration-impacting elements in higher education during the recent pandemic, as well as the significance of SM throughout this approach. We concentrated on the many uses of social media and how they affect the growth of communication skills in a particular online education and learning environment to fill in the gaps in the research indicated above.

We also correlated our findings with those of previous systematic reviews of SM currently in existence and higher education during COVID-19-related research, such as studying social media usage in higher education [66], comparing Microsoft Teams and social network sites during COVID-19 [67], and investigating college students’ use of SM during the COVID-19 pandemic [68]. All of the works have comparable information on the growth of publications over time, indicating a rising demand for social-media-related academic research.

However, the generational and digital divide, as well as the unique features of higher education, may operate as a barrier to students’ ability to collaborate and communicate effectively. There is little research on what motivates cooperation and communication in a distance learning setting. As a result, this work fills in this research gap. First, it offers empirical data on crucial confounding factors that affect students’ collaboration and communication in urgent higher education due to the COVID-19 epidemic. Second, it supports and evaluates the various facets of SM usage and how they affect the growth of soft skills in a particular higher education context. The numerous advantages of using SM for teaching and learning have previously been noted by certain authors, including enhanced performance, easier learning, and greater engagement [69]. More research on social media’s effects is necessary since its use in higher education continues to increase [70].

7. Conclusions

To conclude, papers on SM use and higher education during the recent COVID-19 pandemic were extracted from 519 publications that were indexed in the WoS for the present study. The obtained records were analyzed for their various bibliometric characteristics, such as citation analysis, leading sources, active authors, international collaborations, emerging topics, and mapping of frequently used terms. Scientific maps were created using the VOS viewer tool. The worldwide network of author keywords and the content analysis of the related scientific research has highlighted the main keywords strategies used, such as COVID-19, social media, pandemic, and higher education.

There have been published articles in this area of study in the most prominent journals, such as the International Journal of Environmental Research and Public Health, Sustainability, and Journal of Medical Internet Research. The COVID-19 pandemic’s effects on mental well-being and life quality were discussed in the most often cited study. The United States, China, and the United Kingdom were the top publishing nations according to the examination of the countries. In addition, the inclusion of the literature’s co-occurrence and co-authorship analyses contributed to the exposure of social media in the COVID-19 literature. We presume that our research will help scientists explore new avenues, encourage cross-disciplinary collaboration with other human coronavirus researchers, point young researchers in the direction of untapped areas of study, facilitate the creation and application of new social media in this area for the learning platform, and provide valuable advice about COVID-19 hospitalization, treatment, and avoidance.

8. Limitations and Future Scope for Research

In this research, which has rarely been performed on this scale, research papers published in the field of COVID-19 were conducted worldwide. Only empirical studies from the WOS’s articles were included in the query string for this bibliometric analysis. All documents published between 2019–2021 were included in the study. It is recommended to combine two or more databases, e.g., the WoS, PubMed, and Scopus, for future research to obtain more detailed results. Overall, the findings have significant ramifications for determining how both students and instructors will use social media in higher education over time. Additionally, by shedding light on the expanding significance of social networks in higher education as a proposed study and a means of fostering interdisciplinary collaboration, our bibliometric study contributes to the existing body of research. This study could aid governments, organizations, and research scientists in understanding the field’s big picture and facilitate advanced academics to comprehend how SM tools evolved related to the COVID-19 pandemic in higher education. Decision-makers must also pay close attention to the scholarly institutions in the country, encouraging them to take on new research projects and programs in collaboration with other international organizations in the field of social media literature.