Dataset Supporting a Modeling and Bibliometric Analysis of Fintech in Entrepreneurship (1973-2024)

This dataset supports a bibliometric and modeling analysis on the topic of Fintech in Entrepreneurship covering the period from 1973 to 2024. The dataset was derived from the Scopus database and includes a total of 461 peer-reviewed documents that meet the following clear inclusion criteria: (a) relevance to fintech in entrepreneurship, (b) coverage of a complete publication year, (c) peer-reviewed status, and (d) accessibility for analysis. The dataset comprises metadata from 1108 authors affiliated with institutions in 85 different countries. It contains extensive bibliographic fields such as author names, document titles, publication years, EIDs, source titles, volumes, issues, pages, citation counts, document and source types, publication stages, DOIs, open access status, bibliographic information, affiliations, serial identifiers (e.g., ISSN), PubMed IDs, publishers, editors, languages, correspondence addresses, abbreviated source titles, abstracts, keywords, indexed keywords, funding details, numbers, acronyms, sponsors, funding texts, tradenames and manufacturers, accession numbers and chemicals, and conference information, including references. Bibliometric visualizations were generated using Microsoft Excel and R Biblioshiny. Microsoft Excel was used to visualize main information and annual scientific production, while R Biblioshiny enabled the visualization of main information summaries, thematic maps, and trending topics. In addition, the dataset supports a polynomial regression model (level 2) implemented in Python for forecasting the number of scientific publications from 2025 to 2034. The modeling output includes a projection chart in PNG format, and bibliometric visualizations include images of thematic maps, annual scientific production trends, trend topic maps, and research stage diagrams, also in PNG format. The primary dataset is provided in CSV format and is titled “Fintech in Entrepreneurship Dataset.” This dataset serves as a comprehensive resource for researchers interested in exploring publication trends, thematic developments, and predictive modeling in the interdisciplinary field of fintech and entrepreneurship.