Contemporary commentators describe the current period as “an era of fake news” in which misinformation, generated intentionally or unintentionally, spreads rapidly. Although affecting all areas of ...life, it poses particular problems in the health arena, where it can delay or prevent effective care, in some cases threatening the lives of individuals. While examples of the rapid spread of misinformation date back to the earliest days of scientific medicine, the internet, by allowing instantaneous communication and powerful amplification has brought about a quantum change. In democracies where ideas compete in the marketplace for attention, accurate scientific information, which may be difficult to comprehend and even dull, is easily crowded out by sensationalized news. In order to uncover the current evidence and better understand the mechanism of misinformation spread, we report a systematic review of the nature and potential drivers of health-related misinformation. We searched PubMed, Cochrane, Web of Science, Scopus and Google databases to identify relevant methodological and empirical articles published between 2012 and 2018. A total of 57 articles were included for full-text analysis. Overall, we observe an increasing trend in published articles on health-related misinformation and the role of social media in its propagation. The most extensively studied topics involving misinformation relate to vaccination, Ebola and Zika Virus, although others, such as nutrition, cancer, fluoridation of water and smoking also featured. Studies adopted theoretical frameworks from psychology and network science, while co-citation analysis revealed potential for greater collaboration across fields. Most studies employed content analysis, social network analysis or experiments, drawing on disparate disciplinary paradigms. Future research should examine susceptibility of different sociodemographic groups to misinformation and understand the role of belief systems on the intention to spread misinformation. Further interdisciplinary research is also warranted to identify effective and tailored interventions to counter the spread of health-related misinformation online.
•Studies on health misinformation mainly relate to vaccine and infectious disease.•Findings show high prevalence and popularity of misinformation on social media.•Theoretical frameworks are drawn on disparate disciplinary paradigms.•Studies employed content analysis, social network analysis or experiments.•More interdisciplinary research needed to understand the susceptibility of users.
In this paper, we employ bibliometric analysis to empirically analyse the research on social entrepreneurship published between 1996 and 2017. By employing methods of citation analysis, document ...co-citation analysis, and social network analysis, we analyse 1296 papers containing 74,237 cited references and uncover the structure, or intellectual base, of research on social entrepreneurship. We identify nine distinct clusters of social entrepreneurship research that depict the intellectual structure of the field. The results provide an overall perspective of the social entrepreneurship field, identifying its influential works and analysing scholarly communication between these works. The results further aid in clarifying the overall centrality features of the social entrepreneurship research network. We also examine the integration of ethics into social entrepreneurship literature. We conclude with a discussion on the structure and evolution of the social entrepreneurship field.
•This article summarises the main challenges in the steps of the social media analytics process.•Possible solutions for these challenges are proposed.•We extend the social media analytics framework ...with challenges in the given phases.
Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data is being analysed in many different disciplines. The social media analytics process involves four distinct steps, data discovery, collection, preparation, and analysis. While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on the stages of data discovery, collection, and preparation. To address this gap, we conducted an extended and structured literature analysis through which we identified challenges addressed and solutions proposed. The literature search revealed that the volume of data was most often cited as a challenge by researchers. In contrast, other categories have received less attention. Based on the results of the literature search, we discuss the most important challenges for researchers and present potential solutions. The findings are used to extend an existing framework on social media analytics. The article provides benefits for researchers and practitioners who wish to collect and analyse social media data.
Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used ...during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2.
We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs.
Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001).
IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.
•Conducts a systematic quantitative literature review of industry 4.0 literature.•Develops a holistic framework based on the most recurrent research themes.•Finds seven communities and three research ...clusters using SNA.•Industry 4.0 in services industries is neglected.•Combination of theoretical approaches is necessary to deal with digitized services.
The “industry 4.0" phenomenon is expected to influence almost every aspect of business value chains, and hence it has been increasingly analyzed by management scholars. However, the overarching intellectual structure emerging from this new stream of literature has not yet been synthesized in a framework nor critically discussed. Furthermore, despite being part of the rhetoric in several recent industrial governmental plans, industry 4.0 in service sectors has not been systematically reviewed to date. By leveraging a systematic quantitative literature review, a data-driven approach and a quantitative methodology—embedding both bibliographic coupling and network analysis techniques—this study provides a clear visualization of the emerging intellectual structure of industry 4.0 in management studies. We also develop a framework based on the most recurrent themes emerging from the results of bibliometric and network analyses—the latter could be used by management scholars to understand studies surrounding industry 4.0. As service businesses can create and capture value generated through the 4th Industrial Revolution as well as manufacturing firms, we suggest that scholarly attention should also be directed toward the service industries and provide a research agenda.
With the rapid development of societal and technological paradigms, large-scale group decision making becomes an emerging topic. In conventional group decision making methods, it is often assumed ...that all experts are independent. However, with the expansion of social media, experts usually have some relationships and get together for some reasons such as the academic relationship, working relationship or common interests. In these cases, experts are no longer independent individuals. To address the issue, this study introduces a large-scale group decision making model based on the social network analysis. In this model, experts can provide trust values on other experts. Due to the scale and complexity of the large-scale group decision making problems, the dimensional reduction, which uses community detection to classify experts into local communities, is deemed essential. Based on this process, the whole group can be divided into two layers. The first layer is the global network containing all communities, and the second layer is the local network within a community. This study develops a model to address large-scale group decision-making problems considering the local and global consensus in two layers simultaneously. This model allows experts to use probabilistic linguistic preference relations to express their cognitive complex evaluation information. An illustrative example is presented to show the usefulness of the proposed model.
•Up-to-date literature review of basic research and application domains in social networks.•Definition of a new set of metrics to measure the capacity of SNA frameworks and tools.•Quantitative ...analysis of social network analysis tools and frameworks (SNA).•Evaluation of 20 popular SNA software tools according to the new set of metrics.•SNA software technology assessment.
Social network based applications have experienced exponential growth in recent years. One of the reasons for this rise is that this application domain offers a particularly fertile place to test and develop the most advanced computational techniques to extract valuable information from the Web. The main contribution of this work is three-fold: (1) we provide an up-to-date literature review of the state of the art on social network analysis (SNA); (2) we propose a set of new metrics based on four essential features (or dimensions) in SNA; (3) finally, we provide a quantitative analysis of a set of popular SNA tools and frameworks. We have also performed a scientometric study to detect the most active research areas and application domains in this area. This work proposes the definition of four different dimensions, namely Pattern & Knowledge discovery, Information Fusion & Integration, Scalability, and Visualization, which are used to define a set of new metrics (termed degrees) in order to evaluate the different software tools and frameworks of SNA (a set of 20 SNA-software tools are analyzed and ranked following previous metrics). These dimensions, together with the defined degrees, allow evaluating and measure the maturity of social network technologies, looking for both a quantitative assessment of them, as to shed light to the challenges and future trends in this active area.
Peers become increasingly important socializing agents for academic behaviors and attitudes during adolescence. This study investigated peer influence and selection effects on adolescents' emotional ...(i.e., flow in schoolwork, school burnout, school value), cognitive (i.e., school effort), and behavioral (i.e., truancy) engagement in school. A social network approach was used to examine students of post-comprehensive education in Finland (N = 1419; mean age = 16). Students were asked to nominate peers to generate peer networks and to describe their own school engagement at two time points (one year apart). Network analyses revealed that the degree to which peer influence and selection effects occurred varied by dimension of school engagement. Over time, peers influenced students' emotional, cognitive, and behavioral engagement. Similarity in behavioral engagement, but not in emotional and cognitive engagement, increased the likelihood of forming new peer relationships. Additionally, some of the peer influence and selection effects on school engagement were moderated by student academic achievement.
•Peer effect on school engagement includes influence and selection processes.•School engagement is a multidimensional construct.•Students had a tendency to choose new peers based on earlier similarity in behavioral engagement.•Students became more similar to their peers in terms of emotional, cognitive, and behavioral engagement.•Some peer influence and selection effects on engagement were moderated by achievement.
This paper introduces a relative utility function-based consensus method for three-way group decision (TWGD) in a social network scenario where overlapping subgroups and non-overlapping subgroups ...co-exist. Firstly, we construct a three-way decision (TWD) model rooted in utility theory, which proposes a novel objective calculation method for the relative utility functions based on evaluation values. The relative utility matrices of decision makers (DMs) are derived on this basis. Secondly, a utility and trust-driven overlapping clustering algorithm is designed to maximize the overall trust level and the difference between subgroup clustering centers, aiming to divide the group into several manageable subgroups. In addition, we identify contrarian DMs, triggering a delegation-exit mechanism, and determine the weights of subgroups and DMs. Thirdly, a three-way group consensus decision model is formulated to provide targeted adjustment strategies for different types of DMs. To improve group consensus, we address the influence of key DMs on the opinions of overlapping subgroups with a minimum adjustment consensus model. Finally, we demonstrate the feasibility and scientificity of the proposed method through the illustrative example, sensitivity analysis, and comparative analysis.
•The utility-three-way decision model is further developed for IFVs.•An objective calculation method for determining the relative utility is proposed.•Consider trust and utility information in the overlapping clustering algorithm.•The TWGD consensus model is established considering decision makers' types.
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