2015/03/11 by Sabir Ribas, Berthier Ribeiro‐Neto, Berthier Ribeiro-Neto +9
Computer Science · Physics and Astronomy · #Advanced Clustering Algorithms Research #Complex Network Analysis Techniques #Data Mining Algorithms and Applications #Digital Libraries (cs.DL) #FOS: Computer and information sciences #cs.DL
paper · pdf · doi:10.48550/arxiv.1503.07496
3 pages, 1 figure
arxiv created 2015/03/11 · openalex publication_date 2015/03/11 · arxiv updated 2015/03/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this work we propose a metric to assess academic productivity based on publication outputs. We are interested in knowing how well a research group in an area of knowledge is doing relatively to a pre-selected set of reference groups, where each group is composed by academics or researchers. To assess academic productivity we propose a new metric, which we call P-score. Our metric P-score assigns weights to venues using only the publication patterns of selected reference groups. This implies that P-score does not depend on citation data and thus, that it is simpler to compute particularly in contexts in which citation data is not easily available. Also, preliminary experiments suggest that P-score preserves strong correlation with citation-based metrics.