Mapping the landscape of female entrepreneurship in Africa: trends, networks and hot topic through text mining techniques

Abstract

Purpose The study examines the characteristics and development trends of female entrepreneurship publications, cooperation networks between countries, journals and individuals, intellectual structure of female entrepreneurship studies in Africa and hot research topics. Future comparative studies in different contexts and interdisciplinary collaboration can enrich the understanding about female entrepreneurship research. Design/methodology/approach The authors used text mining to analyze 130 peer-reviewed articles published from 1975 to 2022 for keywords and classify them into eight main classes: (1) Paradoxical space and informality, (2) work–family conflict, (3) women's entrepreneurial identity and networking, (4) rural women's entrepreneurial activities in the agricultural sector, (5) religious belief and women's entrepreneurial practice, (6) financial trap and environmental challenges, (7) women's entrepreneurial intentions and capacity building and (8) women in cultural entrepreneurship. Findings Female entrepreneurship publications develop significantly. Since 1975, African female entrepreneurship study has grown. Results show 130 publications from 1975 to 2023, with two papers published yearly in 2006–2011 and 23 in 2023, indicating growing interest. Paradoxical space and informality, work–family conflict, women's entrepreneurial identity and networking, religious belief and practice, financial trap and environmental challenges and entrepreneurial intentions and capacity building were hot topics identified by topic modeling analysis. Practical implications Female entrepreneurs have looser intellectual networks. Nation, organization and researcher communication is inadequate. Collaborating researchers from different universities and countries may develop the field. Originality/value This study is more data-driven and less biased than earlier reviews because it is based on thousands of citation data rather than a small number of papers pre-selected by the researchers. Displaying the field's structure and evolution enhances previous reviews.