Akademik Veri Yönetim Sistemi
INFORMATION DISCOVERY AND DELIVERY, 2025 (ESCI)
PurposeThe purpose of this paper is to investigate the publishing characteristics of scholars across three popular bibliographic databases, namely, Google Scholar, Web of Science and Scopus, that allow the publication output and impact of scholars to be evaluated from a data-centric perspective.Design/methodology/approachA cluster analysis was conducted on the bibliometric and demographic data of 4,054 scholars, sampled from 23 academic division in seven Turkish universities. Among various clustering algorithms, this study applies Ward's hierarchical clustering method to group scholars based on the publication characteristics. Moreover, this paper conducted cross-analyses on their academic divisions and titles to provide a more comprehensive evaluation of their scholarly performance.FindingsThe cluster analysis resulted in four distinct groups of scholars having different publication and citation patterns across three major databases. The results indicate that for all clusters, there is a decline in scholars' publication performance as this paper move from the Google Scholar database to the Scopus and Web of Science databases. The study results indicate that highly productive and influential scholars are affiliated with Medicine, Natural Sciences and Engineering, while less productive scholars are affiliated with Humanities, Educational Sciences and Administrative, Political and Applied Sciences.Originality/valueThis study contributes to prior literature by exploring and profiling the individual scholar's publication performances in prominent bibliographic databases. It is also precious that the findings of this study offer useful information on scholarly publication characteristics in major databases and can be valuable for policymakers and scholars.