Analyzing research diversity of scholars based on multi-dimensional calculation of knowledge entities

Measuring diversity in research works is critical to the promotion of scientific evaluation. Existing approaches usually focus on quantifying the diverse interdisciplinary states of research fields, lacking fine-grained detection and comparative analysis between different diversity calculation schemas at the level of individual scholars. To clearly recognize essential characters of research content and reflect important research diversity characteristics of scholars, we propose to use entitymetrics analysis for the scholar-level diversity measurement. Compared to disciplines or topics, minimal stable knowledge units embedded in scientific papers have advantages in mining knowledge usage and capturing the microscopic differences among contents. In this study, we compare six diversity calculation schemas based on the three primary properties of entity diversity: variety, balance, and disparity. The comparison demonstrates the usefulness of entities in portraying manifold subject categories, detecting content disparity, and characterizing content distribution patterns of research, which reflects research diversity of scholars in a more granular way. It also points out the respective features, scopes, and application scenarios of each schema, which provides further guidance for selections and appropriate usage of schemas, ultimately fostering the accurate scientific assessment of scholar characteristics (e.g., the cross-disciplinary collaboration potentiality, academic aptitude, multi-subject problem-solving skills).