COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution

Abstract

COVID-19 has been an unprecedented challenge that disruptively reshaped societies and brought a massive amount of novel knowledge to the scientific community. However, as this knowledge flood continues surging, researchers have been disadvantaged by not having access to a platform that can quickly synthesize emerging information and link the new knowledge to the latent knowledge foundation. Aiming to fill this gap, we propose a research framework and develop a dashboard that can assist scientists in identifying, retrieving, and understanding COVID-19 knowledge from the ocean of scholarly articles. Incorporating principal component decomposition (PCD), a knowledge mode-based search approach, and hierarchical topic tree (HTT) analysis, the proposed framework profiles the COVID-19 research landscape, retrieves topic-specific latent knowledge foundation, and visualizes knowledge structures. The regularly updated dashboard presents our research results. Addressing 127,971 COVID-19 research papers from PubMed, the PCD topic analysis identifies 35 research hotspots, along with their inner correlations and fluctuating trends. The HTT result segments the global knowledge landscape of COVID-19 into clinical and public health branches and reveals the deeper exploration of those studies. To supplement this analysis, we additionally built a knowledge model from research papers on the topic of vaccination and fetched 92,286 pre-Covid publications as the latent knowledge foundation for reference. The HTT analysis results on the retrieved papers show multiple relevant biomedical disciplines and four future research topics: monoclonal antibody treatments, vaccinations in diabetic patients, vaccine immunity effectiveness and durability, and vaccination-related allergic sensitization.

Tech mining: a revisit and navigation

“…Examining 177 Web of Science (WoS) abstract records from a search on either “Tech Mining” or “research profiling” – alerts us to some associated keywords: technical intelligence, science mapping, and Semantic TRIZ. From our experience, in recent years, we see increasing Tech Mining engagement of: intelligent bibliometrics (incorporating various AI capabilities) (Zhang et al, 2020 , 2021a ), knowledge modeling (to identify related research, not limited to use of particular terms in searching) (Cassidy, 2020 ; Wu et al, 2023 ), and Literature-Based Discovery (to identify related research falling outside one's topical search domain) (Porter et al, 2020 ; Zhang et al, 2023b ).…”

Technology and Fake News: Shaping Social, Political, and Economic Perspectives

“…The erosion of trust extends beyond media institutions and encompasses various societal establishments. Governments, political parties, and educational systems often fall victim to fake news campaigns, which aim to manipulate public opinion or undermine the legitimacy of these institutions [20]. The dissemination of false narratives erodes trust in these establishments, resulting in a loss of faith in governance, public services, and the democratic process.…”