Bibliometric analyses frequently encounter issues such as duplicate records, missing metadata, and inconsistent formats, reducing reliability and efficiency. Existing solutions offer minimal assistance for automated data integration and enrichment, requiring researchers to rely on manual efforts. This paper presents a Python-based software solution that addresses these challenges by merging datasets from Scopus and Web of Science, performing DOI-based deduplication, and enhancing metadata using APIs such as Unpaywall and Semantic Scholar. BibexPy provides analysis-ready formats that work with VosViewer and Biblioshiny, minimizing human labor and enhancing data quality. It enables advanced analysis like as co-citation mapping and trend identification, promoting innovation in bibliometric research approaches.
Stored only when both papers are in the corpus — 31 citations exist upstream.
Imported from OpenAlex (CC0) — nothing here is generated.