English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

As scientists worldwide search for answers to the overwhelmingly unknownbehind the deadly pandemic, the literature concerning COVID-19 has been growingexponentially. Keeping abreast of the body of literature at such a rapidlyadvancing pace poses significant challenges not only to active researchers butalso to the society as a whole. Although numerous data resources have been madeopenly available, the analytic and synthetic process that is essential ineffectively navigating through the vast amount of information with heightenedlevels of uncertainty remains a significant bottleneck. We introduce a genericmethod that facilitates the data collection and sense-making process whendealing with a rapidly growing landscape of a research domain such as COVID-19at multiple levels of granularity. The method integrates the analysis ofstructural and temporal patterns in scholarly publications with the delineationof thematic concentrations and the types of uncertainties that may offeradditional insights into the complexity of the unknown. We demonstrate theapplication of the method in a study of the COVID-19 literature.

A Glimpse of the First Eight Months of the COVID-19 Literature on Microsoft Academic Graph: Themes, Citation Contexts, and Uncertainties