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PurposeHow to extract useful information from a very large volume of literature is a great challenge for librarians. Topic modeling technique, which is a machine learning algorithm to uncover latent thematic structures from large collections of documents, is a widespread approach in literature analysis, especially with the rapid growth of academic literature. In this paper, a comparison of topic modeling based literature analysis has been done using full texts and s of articles.Design/methodology/approachThe authors conduct a comparison study of topic modeling on full-text paper and corresponding to assess the influence of the different types of documents been used as input for topic modeling. In particular, the authors use the large volumes of COVID-19 research literature as a case study for topic modeling based literature analysis. The authors illustrate the research topics, research trends and topic similarity of COVID-19 research by using Latent Dirichlet allocation (LDA) and topic visualization method.FindingsThe authors found 14 research topics for COVID-19 research. The authors also found that the topic similarity between using full-text paper and corresponding is higher when more documents are analyzed.Originality/valueFirst, this study contributes to the literature analysis approach. The comparison study can help us understand the influence of the different types of documents on the results of topic modeling analysis. Second, the authors present an overview of COVID-19 research by summarizing 14 research topics for it. This automated literature analysis can help specialists in the health and medical domain or other people to quickly grasp the structured morphology of the current studies for COVID-19.
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PurposeThis study aims to reveal the topic structure and evolutionary trends of health informatics research in library and information science.Design/methodology/approachUsing publications in Web of Science core collection, this study combines informetrics and content analysis to reveal the topic structure and evolutionary trends of health informatics research in library and information science. The analyses are conducted by Pajek, VOSviewer and Gephi.FindingsThe health informatics research in library and information science can be divided into five subcommunities: health information needs and seeking behavior, application of bibliometrics in medicine, health information literacy, health information in social media and electronic health records. Research on health information literacy and health information in social media is the core of research. Most topics had a clear and continuous evolutionary venation. In the future, health information literacy and health information in social media will tend to be the mainstream. There is room for systematic development of research on health information needs and seeking behavior.Originality/valueTo the best of the authors' knowledge, this is the first study to analyze the topic structure and evolutionary trends of health informatics research based on the perspective of library and information science. This study helps identify the concerns and contributions of library and information science to health informatics research and provides compelling evidence for researchers to understand the current state of research.
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PurposeAs of December 2021, WeChat had more than 1.2 billion active users worldwide, making it the most active online social media in mainland China. The term social commerce is used to describe new online sales through a mix of social networks and/or peer-to-peer communication or marketing strategies in terms of allowing consumers to satisfy their shopping behaviour through online social media. Thus, given the numerous active users, the development of online social media and social commerce on WeChat is a critical issue of internet research.Design/methodology/approachThis empirical study takes WeChat as the online social media research object. Questionnaires for WeChat users in China were designed and distributed. All items are designed as nominal and ordinal scales (not Likert scale). The obtained data was put into a relational database (N = 2,342), and different meaningful patterns and rules were examined through data mining analytics, including clustering analysis and association rules, to explore the role of WeChat in the development of online social media and social commerce.FindingsPractical implications are presented according to the research findings of meaningful patterns and rules. In addition, alternatives to WeChat in terms of further development are also proposed according to the investigation findings of WeChat users' behaviour and preferences in China.Originality/valueThis study concludes that online social media, such as WeChat, will be able to transcend the current development pattern of most online social media and make good use of investigating users' behaviour and preferences, not only to stimulate the interaction of users in the social network, but also to create social commerce value in social sciences.
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PurposeMobile-based payment is increasing exponentially but in the developing country like India, consumers' perception is highly positive in daily cash transaction. The purpose of this research is to identify and examine the important challenges for mobile wallet (m-wallet) implementation in India. In the wake of COVID-19, one of the transmission mechanisms of this virus has been the coins and paper money passed between a buyer and a seller. As such m-wallet considered as a convenience of payment has become a necessity in light of the pandemic.Design/methodology/approachThe authors explored 19 unique sets of challenges selected from the literature and collected data from 14 experts from private sector, multinational corporations and mixed private and public partnership who have significant knowledge and experience of mobile payment implementation and use in their respective organisations. Also, the authors have used Interpretive Structural Modelling (ISM) methodology in developing a hierarchal model for the identified challenges. The authors implemented Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis to classify the identified challenges.FindingsThe ISM-based framework is divided into nine different hierarchical levels. "Lack of strong regulatory compliance (Ch6)” has been recognised as the most important challenge, which inhibited the mobile wallet implementation, whereas "Perception of customers about the value of using mobile wallets (Ch11)” is the most dependent critical challenge. There are seven hierarchical layers in between the top and the bottom level with the varied number of challenges based on their driving and dependence power.Originality/valueThis is the first research to the best of our knowledge that has not only comprehensively reviewed the m-wallet literature but also employed a unique ISM-MICMAC-based approach to develop a framework of challenges for the m-wallet implementation.
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PurposeThe aim of this study is to investigate how social media users' experience of seeking emergency information affects their engagement intention toward emergency information with a reciprocity framework integrated with information adoption model.Design/methodology/approachDrawing on reciprocity theory, indebtedness theory, and information adoption model, an integrative research model is developed. This study employs a questionnaire survey to collect data of 325 social media users in China. Structural equation modeling analyses are conducted to test the proposed theoretical model.FindingsSocial media users' experience of seeking emergency information has a strong effect on their perceived information usefulness and indebtedness, while perceived information usefulness further influences community norm, indebtedness, and engagement intention. The authors also found that perceived information usefulness mediates the relationships between experience of seeking emergency information and community norm/indebtedness.Originality/valueThis study offers a new perspective to explain social media users' engagement intention in the diffusion of emergency information. This study contributes to the literature by extending the theoretical framework of reciprocity and applying it to the context of emergency information diffusion. The findings of this study could benefit the practitioners who wish to leverage social media tools for emergency response purposes.
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PurposeThis study seeks to explore digital natives' mobile usage behaviors and, in turn, develop an analytic framework that helps articulate the underlying components of mobile addiction syndrome (MAS), its severity levels and mobile usage purposes.Design/methodology/approachThe investigation adopts a survey method and a case study. The results of the former are based on 411 random classroom observations and 205 questionnaire responses, and the insights of the latter are derived from 24 interviews and daily observations.FindingsThe findings validate five distinctive signs that constitute MAS and their significant correlations with each of the Big Five personality traits. Classroom observations confirm the prevalence of addiction tendency among digital natives in the research context. Seven levels of MAS and six different mobile usage purposes further manifest themselves from case analysis. There appears to be a sharp contrast between the addicted and non-addicted groups in their mobile purposes and behavioral patterns. Additionally, family relationships seem influential in shaping non-addictive mobile usage behaviors.Research limitations/implicationsPsychological perspectives on MAS may be important but insufficient. Empirical investigation on a global scale, especially with distinctive cross-cultural comparisons, will be highly encouraged. How MAS evolves over time should also serve as future research interests.Practical implicationsTeaching pedagogy of college education might need certain adjustments to intrigue digital natives' learning interests. Future managers might also need to adopt better performance measurements for digital natives who barely separate work from personal matters in their mobile devices.Social implicationsParents and healthcare institutions may need to develop response mechanism to tackle this global issue at home and in society. The long-term effects of the COVID-19 pandemic on MAS might also deserve global attention.Originality/valueThe analytic framework developed provides an original mechanism that can be valuable in identifying MAS severity and associated behavioral patterns.
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The COVID-19 pandemic has not only affected higher education on a global scale but it has also brought numerous challenges to the higher education community. Although initial responses involved faculties rushing to change their traditional curriculums to fit an online environment, we opine that transitioning contents to an online learning environment is not enough. This article adds to the conversations surrounding the challenges and problems faced by the community and opinions to handle these challenges.
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PurposeThe objective of this study was to analyse the influencing factors of citizens' dissatisfaction with government services during the COVID-19 pandemic to help government departments identify problems in the service process and possible countermeasures.Design/methodology/approachThe authors first used cosine interesting pattern mining (CIPM) to analyse citizens' complaints in different periods of the pandemic. Second, the potential evaluation indices of customer satisfaction were extracted from the hotline business system through a hypothesis analysis and modelled using multiple regression analysis. During the index transformation and standardization process, a machine-learning algorithm of clustering and emotion analysis was adopted. Finally, the authors used the random forest algorithm to evaluate the importance of the indicators and obtain the indicators more important to citizen satisfaction.FindingsThe authors found that the complaint topic, appeal time, urgency of citizens' complaints, citizens' emotions, level of detail in the case record, and processing timeliness and efficiency significantly influenced citizens' satisfaction. When the government addresses complaints in a more standardized and efficient manner, citizens are more satisfied.Originality/valueDuring the pandemic, government departments should be more patient with citizens, increase the speed of the case circulation and shorten the processing period of appeals. Staff should record appeals in a more standardized manner, highlighting themes and prioritizing urgent cases to appease citizens and relieve their anxiety.
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PurposeThis research studies the influence of the COVID-19 pandemic on the operation management of Hong Kong academic libraries for understanding the difficulties and challenges for librarians to adapt to the special arrangements during the pandemic.Design/methodology/approachQualitative semi-structured interviews were conducted with librarians in major universities and higher education institutions of Hong Kong. Participants were interviewed either in the face-to-face format or text-based format.FindingsParticipants provided a broad scope about the actual library management and operation changes during the COVID-19. According to the respondents, the most challenging problem for librarians during COVID-19 was to strike a balance between concerns of library staff and users. While they described how these arrangements and changes affected the service quality of academic libraries from different perspectives, the pandemic situation also brought some opportunities, such as pushing the digitalization of all collections and using online resources for future development. A hybrid model for library service would be more common in the future with more demands toward online resources and digital collection, in which academic libraries should be prepared after the pandemic.Originality/valueThis paper provided broad insights into library management and the future development of academic libraries for the post-COVID-19 period. There are scant studies of this topic, especially in an Asian metropolis context with dense population, small campus and limited library physical spaces.
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PurposeThis study investigated the relationship between generalised trust and psychological well-being in college students, considering the social support obtained from their social networks via Twitter and face-to-face (FTF) interactions. Initially, the authors planned to collect data at the beginning of the first semester in 2019 for fine-tuning the model as a pilot study, and in 2020 for the main study. However, due to the coronavirus disease 2019 (COVID-19) pandemic, the data helped authors to analyse changes in young people's psychological situation before and during the pandemic in Japan.Design/methodology/approachThe study conducted a self-report survey targeting college students in the Kanto region in Japan. Data were collected from mid-May to the end of June 2019, as well as in early to mid-June 2020, with 304 and 584 responses, respectively. The collected data were analysed using structural equation modelling and a multiple regression analysis.FindingsThe findings using the 2019 data set indicated that (a) students mostly used Twitter for information gathering and sharing of hobbies, and they received both informatics and emotional support from Twitter, and from FTF interactions;(b) there were direct positive effects of generalised trust and social skills on their psychological well-being;and (c) students with lower levels of generalised trust tended to interact with very intimate individuals using Twitter to obtain social support, which did not have any effects on their improvement of psychological well-being. From the 2020 data set, the authors also found that, like 2019, generalised trust and social skills had direct effects on the improvement of psychological well-being. Additionally, we observed that students spent more time using Twitter and received more emotional support from it, as most people tried not to meet other people in person due to the first State of Emergency in Japan. Similarly, the authors found that in 2019, only social support from very intimate partners via FTF communication had slightly significant effects on improving their psychological well-being, whereas in 2020, their expectation for social networks via FTF had decreased their levels of psychological well-being, but their social support from Twitter had slightly significant effects on their improvement of psychological well-being. One of the main reasons for this might be due to the challenge of meeting with others in person, and therefore, social support from Twitter partially played a role that traditionally was only beneficial through FTF communication.Originality/valueWe understand that this is one of the few social psychological studies on social media that collected data both before and during the COVID-19 pandemic. It provides unique evidence in demonstrating how the COVID-19 pandemic has changed college students communication behaviours.
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PurposeDuring the coronavirus disease 2019 (COVID-19) pandemic, museums, as public gathering places for citizens, have encountered unprecedented difficulties due to limitations to operate as usual for their traditional exhibitions and curations. Thus, museums made corresponding emergency attempts to accelerate digital resource and service platform constructions. Such difficulties aroused many potential problems with the applicability of electronic resources and the mismatch between user expectations and museum services. This study investigates the challenges faced by Hong Kong museums under COVID-19, emergency responses and deliberate practices of Hong Kong museums from the perspective of both museum staff and visitors, and COVID-19's influence on the roles and functions of Hong Kong museums.Design/methodology/approachQualitative interviews with museum staff and visitors were conducted to collect opinions and experiences in the construction and maintenance of museums during the pandemic. Further thematic analyses of museum websites, evaluations, and suggestions were formulated guided by the PEST (Political, Economic, Social, Technological) and AIDA (Attention, Interest, Desire, Action) models.FindingsFindings revealed many online interactions and offline renovations, but the perceptions of visitors and staff differed considerably. While online resources and virtual museums were expanded and well received, long-term prohibitions and repressions drove physical visit desire. Participants emphasized finding a balance between user expectations and realistic practices.Originality/valueScant studies focus on the impact of COVID-19 on the cultural industry, especially in East Asia. This study also highlights new practices of digitalization and the challenges of functional transformation. The authors' findings and suggestions provide hints to optimize the curation of information resources and improve museum service quality in the new digital era. This study also serves as a reliable and meaningful record of COVID-19 impacts on Hong Kong museums.
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PurposeVirtual reality (VR) technology is a potential tool for tourism marketers to maintain the attractiveness of their destinations and recover from the COVID-19 pandemic. However, the effectiveness of VR technology in motivating potential tourists' visit intention under lockdown conditions remains unknown. An integrated model based on the experience economy framework and mood management theory was, therefore, used to explain how tourists' VR experiences affect their mood management processes and subsequent behaviors. This research also examined how perceived travel risk influenced the relationship between mood management processes and future decisions.Design/methodology/approachThis study used a cross-sectional design based on a sample collected from a Chinese survey company, Sojump. The author surveyed 285 respondents who had experienced VR tourism activities during the COVID-19 pandemic. The research model was tested using partial least squares–structural equation modeling.FindingsThe results demonstrated that the four dimensions of VR experiences differently affected mood management processes, while perceived travel risk differently moderated the influence of mood management processes on visit intention and VR stickiness. This provides insights for tourism marketers to adapt to the current tourism environment and develop recovery strategies.Originality/valueIn response to gaps in the literature, this research examined the effectiveness of VR technology in driving tourists' visit intention during the COVID-19 pandemic, providing insights for tourism marketers to successfully implement VR tourism and plan timely recovery strategies.
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PurposeThis study focused on parents' health anxiety by proxy about their children when they started learning online during the COVID-19 pandemic, to explore the impact of academic stress by parent-proxy on parents' learning support services with the mediating role of health anxiety by parent-proxy and the moderating role of parental educational level.Design/methodology/approachIn total, 8,940 primary school students' parents participated in the study. Bootstrapping was performed to test the constructed model.Findings(1) Academic stress by parent-proxy positively predicted health anxiety by parent-proxy. (2) Health anxiety by parent-proxy significantly positively predicted learning support services. (3) Academic stress by parent-proxy also significantly positively predicted learning support services. (4) Academic stress by parent-proxy positively predicted parents' learning support services through the mediating effect of health anxiety by parent-proxy. (5) Parental educational level moderated the relationship between academic stress by parent-proxy, health anxiety by parent-proxy, and learning support services. Academics and parents will benefit from the conclusions of this study in both theory and practice.Originality/valueDuring the COVID-19 pandemic, offline learning has been replaced with online learning, which has brought with it many physical and mental health problems, including additional academic stress. Most studies on learning support services have focused on offline learning. However, this study explored the relationships between academic stress by parent-proxy, health anxiety by parent-proxy, learning support services, and parental educational level in the context of online learning. Results show that it is necessary to pay attention to academic stress and health to provide children with appropriate learning support services.
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PurposeThis study explored the students' perception of their adoption and acceptance of virtual learning (VL), the factors affecting the adoption of educational technologies and the correlation between their intention, perceived behavioral control and care competence in caring for older adults.Design/methodology/approachA cross-sectional survey was conducted. Surveys were administered to evaluate the participants who were involved in VL on geriatric care during coronavirus disease 2019 (COVID-19) pandemic. A total of 315 nursing students participated in the survey, and 287 valid questionnaires were collected (response rate: 91.11%).FindingsA total of 287 participants (mean age 21.09, SD 1.44 years;242/287, 84.3% female) were included in the study. The variables of intention to use technologies were positively correlated with care competence (r = 0.59, p < 0.001). The results revealed that the major predictors were perceived ease-of-use (PEOU) (β = 0.28, 95% confidence interval (CI) 0.16–0.40) and perceived usefulness (PU) (β = 0.22, CI 0.09–0.35) which were significantly positive predictors of competence in geriatric care.Research limitations/implicationsNursing students lack in clinical knowledge and situational experience in geriatric care;therefore, their perceptiveness, expressions and reflection on the process of providing care to hospitalized older patients should be increased. These results indicated that students improved in geriatric healthcare after/during the VL program during COVID-19 pandemic.Originality/valueIt is hoped that the present study would make an invaluable contribution to existing research on education in general and on the quality of care in geriatric nursing as limited studies have been published so far.
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PurposeCommunity health is placed under the limelight during the COVID-19 crisis, providing a unique context for investigating citizens' health-privacy tradeoff in accepting social surveillance technology. To elucidate this tradeoff dilemma, an extended privacy calculus framework integrated with the Health Belief Model, legislative protection, and individual collectivism was examined using the case of national contact-tracing apps.Design/methodology/approachThe hypotheses were tested through PLS-SEM analysis with data collected from a survey on Bluezone – a national app in Vietnam.FindingsThe results indicated the negative impact of privacy concerns, which was offset by the positive effect of perceived benefits in using contact-tracing apps. The effect size of perceived benefits on usage frequency was twice as large as that of privacy concerns. Individual collectivism was revealed as a mitigator of the tradeoff dilemma, as it was positively associated with perceived benefits, whereas legislative protection had no such role. Citizens may perceive legislation protection as invalid when the technologies are developed, implemented, and monitored by the authorities.Originality/valueThe theoretical contributions lie in the extension of the privacy calculus model as well as its application in the context of mobile health apps and surveillance technology. The study empirically corroborated that the privacy calculus theory holds when technologies move along the pervasiveness spectrum. This study also provided actionable insights for policymakers and developers who advocate the mass acceptance of national contact-tracing apps.
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PurposeThe lockdown of libraries has led to changes in the delivery of services. Reviewing many studies in this regard appears to be of great importance. Thus, this study aims to analyze the articles related to libraries and COVID-19 using the co-occurrence analysis.Design/methodology/approachThe current study is applied in terms of purpose and scientometrics in terms of type, which has been conducted using a retrospective bibliometric analysis method and drawing a science map. The relevant keywords were searched in the Scopus and 225 articles were reviewed in terms of author, year of publication, journal, organization and subject. Then, the VOSviewer software was used to analyze and illustrate the keywords and draw the scientific map of the articles.FindingsThe results showed that 225 articles by 496 authors from 66 countries and 379 organizations were published in the subject area of libraries and COVID-19. These articles have received 620 citations. The co-occurrence analysis of words showed that these scientific productions are classified into four clusters: "The role of libraries and librarians”, "The use of media, social network and communication technologies in order provide library services”, "Online Library Services” and "Infodemic and misinformation in the COVID-19 Pandemic”.Originality/valueIt is the first time during the COVID-19 pandemic that a scientific map has been drawn up of studies that have examined the role of libraries in this pandemic. The results of the present study may help libraries to access what they need to consider in any crisis.
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Organizations have encountered risks of all types dealing with information systems (IS) and information technology (IT). However, managing risks in the COVID-19 environment is not something organizations have encountered in the past, at least to the extent. This paper identifies a number of IS/IT-related risks focusing on the current coronavirus environment. Suggestions are provided for managers on how they might recognize and minimize these risks.
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PurposeThe feasibility of process mining combined with simulation techniques in estimating the effectiveness of COVID-19 prevention strategies on infection and mortality trends to determine best practices is assessed in this study. The quarantine event log is built from the CUSP (the COVID-19 US State Policy) database, where the dates of implemented social policies in the USA to respond to the COVID-19 pandemic are documented.Design/methodology/approachCOVID-19 is a highly infectious disease leading to a very high death toll worldwide. In most countries, the governments have resorted to a series of drastic strategies to prevent the outbreak by restricting the activities and movement among their population for a predefined time. Heretofore, different approaches have been published to estimate quarantine strategies and the majority signify the positive effect on managing this pandemic. Notably, the process perspective of COVID-19 datasets is of less concern among researchers. The purpose of this paper is to exploit the process mining techniques to model and analyze the quarantine implementation processes.FindingsThe discovered process model has 51 process variants for 51 cases (states), which indicate the quarantine activities were executed in different orders and periods during the pandemic. The time interval analysis between activities reveals the states with the most extended quarantine periods. These primary process mining insights are applied to define scenarios and variables of an agent-based model. The simulation findings indicate a meaningful relation between enforcing quarantine strategies and a declining trend of infection by 90% in the case of following strict quarantine and mask mandates. It is observed that in the post-quarantine period, the disease repeats its ascending trend unless implementation of different intervention strategies likes vaccination.Originality/valueThis study is the first in introducing process mining techniques in analyzing the COVID-19 quarantine strategies impact. The findings provide valuable insights for policymakers to proper control strategies and the process mining research community in expanding more process-related analysis on this pandemic. Also, the results have broad implications for research in other fields like information science to estimate the impact of quarantine strategies on process patterns in library systems.
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PurposeUsing science mapping analysis approach and co-word analysis, the present study explores and visualizes research fields and thematic evolution of the coronavirus. Based on this method, one can get a picture of the real content of the themes in the mentioned thematic area and identify the main minor and emerging themes.Design/methodology/approachThis study was conducted based on co-word science mapping analysis under a longitudinal study (from 1988 to 2020). The collection of documents in this study was further divided into three subperiods: 1988–1998, 1999–2009 and 2010–2020. In order to perform science mapping analysis based on co-word bibliographic networks, SciMAT was utilized as a bibliometric tool. Moreover, WoS, PubMed and Scopus bibliographic databases were used to download all records.FindingsIn this study, strategic diagrams were demonstrated for the coronavirus research for a chronological period to assess the most relevant themes. Each diagram depended on the sum of documents linked to each research topic. In the first period (1988–1998), the most centralizations were on virology and evaluation of coronavirus structure and its structural and nonstructural proteins. In the second period (1999–2009), with due attention to high population density in eastern Asia and the increasing number of people affected with the new generation of coronavirus (named severe acute respiratory syndrome virus or SARS virus), publications have been concentrated on "antiviral activity.” In the third period (2010–2020), there was a tendency to investigate clinical syndromes, and most of the publications and citations were about hot topics like "severe acute respiratory syndrome,” "coronavirus” and "respiratory tract disease.” Scientometric analysis of the field of coronavirus can be regarded as a roadmap for future research and policymaking in this important area.Originality/valueThe originality of this research can be considered in two ways. First, the strategic diagrams of coronavirus are drawn in four thematic areas including motor cluster, basic and transversal cluster, highly developed cluster and emerging and declining cluster. Second, COVID-19 is mentioned as a hot topic of research.