Evaluating the Academic Performance of Institutions within Scholarly Communities
Most state-of-the-art studies either conduct peer assessment or adopt bibliometric indicators for institution evaluation. However, peer assessments are labor intensive and time consuming, and existing bibliometric methods may produce a biased evaluation result because they do not synthetically model many crucial factors that reflect the academic performance of institutions in a unified way. Thus,we propose a factor graph-based institution ranking model to leverage institutions’ individual information (i.e., quantitative and qualitative information) and scholarly network information (i.e., collaborative intensity) in this paper. We choose the peer assessment result from the best-known U.S. News & World Report as the ground truth and conduct a case study on the U.S. institution ranking in the library and information science (LIS) research field. The experimental results indicate that our approach can be a better alternative for the manual peer assessment for institution evaluation when compared with existing bibliometrics methods.
KeywordsInstitution evaluation academic performance scholarly network factor graph
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