Nisa Bakkalbasi
Papers
1
Total Citations
3
H-Index
1
About
Nisa Bakkalbasi is a research librarian and information scientist whose work centers on the evaluation of automated systems for identifying open access (OA) scholarly content. Her most-cited study, “Evaluation of Algorithm Performance on Identifying OA” (2005, 3 citations), provides a foundational signal-detection analysis of a robot’s accuracy in tagging OA articles. By manually verifying the robot’s classifications, Bakkalbasi and her team revealed a significant tendency to overcode for OA—finding, for example, that 40% of identified OA articles in a biology sample were false positives. This critical contribution highlights the gap between automated metadata generation and ground-truth verification, informing best practices for OA discovery tools and repository management. While her citation count is modest, the work’s methodological rigor has influenced subsequent evaluations of algorithmic performance in scholarly communication. Bakkalbasi’s research underscores the importance of human oversight in digital library systems, making her a thoughtful voice in the ongoing effort to improve the reliability of open access infrastructure.
Research Focus
Key Achievements
Top Papers
- 1Evaluation of Algorithm Performance on Identifying OA3 citations · 2005