A Prediction Method of Publication Productivity for Researchers

Publication productivity affects nearly every aspect of researchers’ scientific career, whereas it is difficult to be predicted due to diversity in researchers’ productivity patterns. This study proposed a model for the publication dynamics of researchers. The model is based on Lotka’s law as well as the relationship between the annual number of publications and time given a historical number of publications. The law and the statistical significance of the relationship are validated by applying them to the high-quality dblp data set. The model allows to predict the number of publications for research groups, and its effectiveness is tested on the data set by fine fittings on the distribution of the number of publications for researchers, the evolutionary trend of their publication productivity, and the probability of producing publications. Due to its nature of regression, the model has the potential to be extended to assess the confidence level of the prediction results and thus would be useful for other empirical research.