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Graphene is a rising star as one of the promising materials with many applications. Its global literature increased fast in recent years. In this work, bibliometric analysis and knowledge visualization technology were applied to evaluate global scientific production and developing trend of graphene research. The data were collected from 1991 to 2010 from the Science Citation Index database, Conference Proceeding Citation Index database and Derwent Innovation Index database integrated by Thomson Reuters. The published papers from different subjects, journals, authors, countries and keywords distributed in several aspects of research topics proved that graphene research increased rapidly over past 20 years and boosted in recent 5 years. The distinctions in knowledge map show that the clusters distributed regularly in keywords of applied patents in recent 5 years due to the potential applications of graphene research gradually found. The analytical results provided several key findings of bibliometrics trend.

Purpose The purpose of this paper is to explore the factors influencing people’s health knowledge adoption in social media, with an eye toward promoting health information literacy and healthy behavior. Design/methodology/approach Based on the integration of sense-making theory, social influence theory, information richness theory, fear appeal theory, and ELM (elaboration likelihood method), a health knowledge adoption model is constructed. Taking spondylopathy as an example, high health threat and low health threat experiments and questionnaires are designed to complete the empirical study. In all, 355 effective survey samples are collected and analyzed, leveraging a partial least squares method. Findings Research results indicate that perceived knowledge quality, perceived knowledge consensus, and perceived source credibility have positive effects on health knowledge adoption via the mediator – trust; knowledge richness contributes to the perception of knowledge quality, source credibility, and knowledge consensus, especially under high health threat; health threat has significant positive moderating effects on the relationship between trust and health knowledge adoption, and the relationship between perceived knowledge quality and trust, with negative moderating effects on the relationships between perceived knowledge consensus, perceived source credibility, and trust. Originality/value This paper examines the mediating effecting of trust in the process of health knowledge adoption. Based on the integration of fear appeal theory, social influence theory, sense-making theory, information richness theory and elaboration likelihood model, this study investigates the factors influencing health knowledge adoption in social media from the perspective of a user, and explores the moderating effect of health threat on health knowledge adoption.

Background The COVID-19 infodemic has been disseminating rapidly on social media and posing a significant threat to people’s health and governance systems. Objective This study aimed to investigate and analyze posts related to COVID-19 misinformation on major Chinese social media platforms in order to characterize the COVID-19 infodemic. Methods We collected posts related to COVID-19 misinformation published on major Chinese social media platforms from January 20 to May 28, 2020, by using PythonToolkit. We used content analysis to identify the quantity and source of prevalent posts and topic modeling to cluster themes related to the COVID-19 infodemic. Furthermore, we explored the quantity, sources, and theme characteristics of the COVID-19 infodemic over time. Results The daily number of social media posts related to the COVID-19 infodemic was positively correlated with the daily number of newly confirmed (r=0.672, P<.01) and newly suspected (r=0.497, P<.01) COVID-19 cases. The COVID-19 infodemic showed a characteristic of gradual progress, which can be divided into 5 stages: incubation, outbreak, stalemate, control, and recovery. The sources of the COVID-19 infodemic can be divided into 5 types: chat platforms (1100/2745, 40.07%), video-sharing platforms (642/2745, 23.39%), news-sharing platforms (607/2745, 22.11%), health care platforms (239/2745, 8.71%), and Q&A platforms (157/2745, 5.72%), which slightly differed at each stage. The themes related to the COVID-19 infodemic were clustered into 8 categories: “conspiracy theories” (648/2745, 23.61%), “government response” (544/2745, 19.82%), “prevention action” (411/2745, 14.97%), “new cases” (365/2745, 13.30%), “transmission routes” (244/2745, 8.89%), “origin and nomenclature” (228/2745, 8.30%), “vaccines and medicines” (154/2745, 5.61%), and “symptoms and detection” (151/2745, 5.50%), which were prominently diverse at different stages. Additionally, the COVID-19 infodemic showed the characteristic of repeated fluctuations. Conclusions Our study found that the COVID-19 infodemic on Chinese social media was characterized by gradual progress, videoization, and repeated fluctuations. Furthermore, our findings suggest that the COVID-19 infodemic is paralleled to the propagation of the COVID-19 epidemic. We have tracked the COVID-19 infodemic across Chinese social media, providing critical new insights into the characteristics of the infodemic and pointing out opportunities for preventing and controlling the COVID-19 infodemic.

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