SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search
This addresses the problem for researchers overwhelmed by the rapid growth of COVID-19 papers, offering a tool for discovery rather than targeted search, though it is incremental as it builds on existing exploratory search methods.
The authors tackled the challenge of navigating the vast COVID-19 research literature by developing SciSight, a system for exploratory search that integrates faceted navigation and research group detection, resulting in over 15,000 users and 42,000 page views with a 13% return rate.
The COVID-19 pandemic has sparked unprecedented mobilization of scientists, generating a deluge of papers that makes it hard for researchers to keep track and explore new directions. Search engines are designed for targeted queries, not for discovery of connections across a corpus. In this paper, we present SciSight, a system for exploratory search of COVID-19 research integrating two key capabilities: first, exploring associations between biomedical facets automatically extracted from papers (e.g., genes, drugs, diseases, patient outcomes); second, combining textual and network information to search and visualize groups of researchers and their ties. SciSight has so far served over $15K$ users with over $42K$ page views and $13\%$ returns.