P-score: A Publication-based Metric for Academic Productivity

TL;DR

The paper introduces P-score, a new publication-based metric for evaluating academic productivity that relies solely on publication patterns and venue weights, making it simpler and less dependent on citation data.

Contribution

It proposes the P-score metric, which assesses academic productivity using publication data and reference groups, avoiding citation data dependence.

Findings

P-score correlates strongly with citation-based metrics.

P-score is easier to compute without citation data.

Preliminary experiments validate P-score's effectiveness.

Abstract

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.