A team at the will be able to start building a valuable new academic research citation tool with newly awarded grant funds from the Institute of Museum and Library Services (IMLS).
Bei Yu
Assistant Professor has been awarded a three-year grant from the totaling $386,030. The grant will fund the project, “Citation Opinion Retrieval and Analysis” (CORA). The work will consist of building of a plug-in tool for digital libraries that will help researchers obtain citation statements about published literature and analyze and classify citations to assist and expedite research much more easily and quickly.
The grant will fund a team of doctoral and graduate students in the building, testing and assessment of an automated tool that can plug into a full-text bibliographic database. The tool will be able to extract citation statements toward a cited article, separate substantial citations from perfunctory ones and categorize substantial citation opinions by their purposes, according to Yu. CORA would also sort and categorize citation opinions by their purposes (such as comparison or critique), subjects (methods, results) and tones (such as positive, negative and neutral), Yu says.
The tool is expected to save librarians and researchers significant amounts of time in finding the most useful comments from a large number of citations, she says.
“As a researcher, if you are looking into a theory, or an algorithm, or a treatment, you would naturally wonder what other researchers think of it. In scholarly communication, researchers express their opinions toward related work through citation statements,” Yu says. “However, manually retrieving and summarizing citation opinions becomes an impossible task with the exponential growth of scientific publications and their citations.”
The retrieval and analysis tool will be designed to provide a new qualitative approach for assessing research impact. It also will help to monitor the quality of scientific publications by facilitating easier identification of citation bias, when citations to positive results overpopulate the citation network, Yu notes.
The grant is one of just four research projects to be awarded grants this year in the IMLS Early Career Research category.
