Chitosan has attracted increasing attention from researchers in the pharmaceutical and biomedical fields as a potential agent for the prevention and treatment of infectious diseases. However, identifying the development of emerging technologies related to this biopolymer is difficult, especially for newcomers trying to understand the research streams. In this work, we designed and implemented a research process based on a bibliometric predictive intelligence model. Our aim is to glean detailed scientific and technological trends through an analysis of publications that include certain word phrases and related research areas. Cross correlation, factor mapping, and the calculation of “emergent” scores were also used. A total of 1,612 scientific papers on chitosan technology related to viral disease treatment published between 2010 and 2020 were retrieved from the Web of Science. Results from the keyword modelling quantitatively highlight three major frontier research and development topic groups: drug delivery and adjuvants, vaccines and immune response, and tissue engineering. More specifically, the emergent scores show that much of the chitosan-based treatment for viral diseases is in the in vitro stage of development. Most chitosan applications are in pharmacology/pharmacy and immunology. All results were confirmed by experts in the field, which indicates that the validated process can be applied to other fields of interest.

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As a global pandemic threatens health and livelihoods, finding effective treatments has become a vital issue that requires worldwide collaboration. This study examines research collaboration and network profiles through a case study of coronavirus diseases, including both the extinct severe acute respiratory syndrome coronavirus (SARS-CoV) and the emerging species (SARS-CoV-2). A scientometric process was designed to apply quantitative tools and a qualitative approach employing technological expertise to accomplish a three-level collaboration analysis. The text mining software, VantagePoint, was used to analyze research articles from the Web of Science database to identify the key national, organizational, and individual players in the coronavirus research field combined with indicators, namely, the breadth and depth of collaboration. The results show that China and the United States are at the center of coronavirus research networks at all three levels, including many endeavors involving single or joint entities. This study demonstrates how governments, public sectors, and private sectors, such as the pharmaceutical industry, can use scientometric analysis to gain insight into the holistic research trends and networks of players in this field, leading to the formulation of strategies to strengthen research and development programs. Furthermore, this approach can be utilized as a visualization and decision support tool for further policy planning, identification and execution of collaboration, and research exchange opportunities. This scientometric process should be directly applicable to other fields.INDEX TERMS bibliometrics, scientometrics, network analysis, research collaboration, coronavirus.

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In accordance with the UN Sustainable Development Goals (SDGs), several SDGs target global food issues, including zero hunger (food security and sustainable agriculture), responsible consumption and production (food losses), climate action (greenhouse gas emissions from food waste), and partnerships for the goals (research collaboration). As such, it is vital to identify technology and market opportunities to support advanced development by exploring scientific and technological research on such SDGs. The significance of technological innovation and evaluations of activity, productivity, and collaboration aids and guides future research streams. Motivated by the growing severity of the global food waste crisis, this paper focuses on the case study of shelf-life extension technology for food and applies a scientometric analysis of patents based on text mining. VantagePoint was used to analyze 2516 patents issued between 2000 and 2020, with the aim of understanding the conceptual structure of knowledge and the social relationships among key players. The results indicate that the technology is experiencing a period of growth, and it can be clustered into five technology sectors. Across all technology clusters, China outperformed other countries in terms of the number of patents. Almost all of China’s patents applied for technology commercialization domestically, whereas other countries tended to apply for patents overseas to exploit opportunities. The findings have implications for both policymaking and strategic decision-making using a multi-layered network innovation system.