Information Engineering for Data-Driven Analysis of h-Index Formation Across Academic Career Stages Using Large-Scale Bibliometric Parameters, Statistical and Clustering Methods

In the context of globalisation of the scientific space and the growing role of scientometric indicators, the Hirsch index (h-index) remains one of the key tools for assessing scientific performance.At the same time, the influence of individual factors on the h-index varies significantly across the stages of a scientist's academic career, necessitating their comparative analysis.The purpose of this work is to conduct a comparative study of the Hirsch index and the factors that influence its formation, considering both novice and experienced scientits anaccounting for The study employed descriptive statistics, visual analysis, time-series smoothing (Kendall's method, Pollard's method, exponential and median smoothing), correlation analysis (Pearson's coefficients), and the k-means clustering method.The study was conducted on two large datasets representing novice and experienced scientists.It was found that the average h-index of experienced scientists is 37.78, approximately 2.6 times that of beginner scientists (14.59).Correlation analysis revealed a weak or negative relationship between the h-index and self-citation, with the strongest correlation observed between the h-index and co-authorship (r = 0.68-0.80).Medium identified 6 clusters, including one that unites scientific leaders with extremely high H-index values.The study's results confirm that, in the early stages of a scientific career, geographical and institutional factors play a significant role.In contrast, for experienced Information Engineering for Data-Driven Analysis of h-Index Formation Across Academic Career Stages Using Large-Scale Bibliometric Parameters, Statistical and Clustering Methods 160Volume 18 (2026), Issue 1 scientists, the Hirsch index becomes more predictable and is determined by the quality of scientific publications, the level of citation, and practical cooperation within scientific teams.