Entrepreneurship has become a central, multidisciplinary, and rapidly expanding research domain, reflecting its relevance to opportunity recognition, new venture creation, innovation, and value creation across economic, social, technological, and institutional contexts (Gartner, 1988; Hoskisson et al., 2011; Kuratko & Covin, 2025; Shane & Venkataraman, 2000). However, despite this expansion, entrepreneurship research remains fragmented, with much scholarship focusing on specific subdomains rather than offering integrated assessments of the field as a whole (Hoskisson et al., 2011; Wurth et al., 2022). This study addresses this gap by providing a large-scale mapping of consolidated research patterns and emerging trends in entrepreneurship research. Using Natural Language Processing (NLP) and Latent Dirichlet Allocation (LDA) topic modeling (Blei et al., 2003), the study analyzes abstracts from 72,039 peer-reviewed articles retrieved from Web of Science and Scopus and published up to 2024. The analysis combines a full-corpus topic modeling approach to identify consolidated research patterns with a more recent-period analysis of publications from 2020 to 2024 to detect emerging trends and thematic shifts that indicate evolving academic priorities. The findings identify eight consolidated research patterns: Social Entrepreneurship and Social Change Research, Female Entrepreneurship and Individual Experiences Research, Innovation and Business Strategy Research, Entrepreneurial Education and Skills Development Research, Entrepreneurial Performance and Outcomes Research, Entrepreneurship and Public Policy Research, Local and Sustainable Entrepreneurship Research, and Entrepreneurship Theory, Context, and Field Development Research. In addition, five emerging trends were identified: Entrepreneurial Education and Skills Training Research, Entrepreneurship and Digital Transformation Research, Female Entrepreneurship and Corporate Performance Research, Entrepreneurship and Social Innovation Research, and Immigrant Entrepreneurship and Cultural Identity Research. These results show that entrepreneurship research is simultaneously anchored in long-standing theoretical foundations and increasingly shaped by digital, gendered, social, educational, sustainability-oriented, policy-related, and migration-related transformations. The study contributes by integrating historical consolidation and contemporary change within a single analytical framework. It also demonstrates the methodological value of NLP and LDA for synthesizing large-scale scientific production and identifying future research opportunities. Future studies should update the corpus longitudinally and complement abstract-level topic modeling with full-text analyses. References Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3(1), 993–1022. https://jmlr.org/papers/v3/blei03a.html Gartner, W. B. (1988). “Who is an entrepreneur?” Is the wrong question. American Journal of Small Business, 12(4), 11–32. https://doi.org/10.1177/104225878801200401 Hoskisson, R. E., Covin, J., Volberda, H. W., & Johnson, R. A. (2011). Revitalizing entrepreneurship: The search for new research opportunities. Journal of Management Studies, 48(6), 1141–1168. https://doi.org/10.1111/j.1467-6486.2010.00997.x Kuratko, D. F., & Covin, J. G. (2025). Fifty years of entrepreneurship: Recalling the past, examining the present, & foreshadowing the future. Journal of Business Research, 186, Article 114980. https://doi.org/10.1016/j.jbusres.2024.114980 Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217–226. https://doi.org/10.5465/amr.2000.2791611 Wurth, B., Stam, E., & Spigel, B. (2022). Toward an entrepreneurial ecosystem research program. Entrepreneurship Theory and Practice, 46(3), 729–778. https://doi.org/10.1177/1042258721998948

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Entrepreneurship,Research patterns,Research trends,Natural language processing (NLP),Latent dirichlet allocation (LDA),Bibliometric analysis