The objective of this study is to analyse domestic research trends in the social economy using text mining techniques: Focus on social enterprises and social ventures

Social enterprises and social ventures, which constitute the actors of the social economy, are assuming the role of the 'third sector' by addressing a multitude of social issues that are not addressed by public and private companies. In this context, it is meaningful to gain an understanding of the characteristics of the social economy and the areas of study that fall within its remit. Accordingly, this study examines the defining characteristics and current research trends of social enterprises and social ventures, two pivotal entities within the social economy. Furthermore, it employs big data methods to analyse extensive data sets pertaining to social enterprises and social ventures. The abstracts of academic research on social enterprises and social ventures were extracted from the Research Information Service (RISS). Subsequently, three analytical techniques were employed in sequence: 1) word frequency and TF-IDF analysis, 2) co-occurrence network analysis, and 3) LDA-based topic modelling analysis. The results of the word frequency and TF-IDF analysis indicate that the economic aspects of social enterprises and their analysis represent a significant research area. Additionally, it can be concluded that research on organisational characteristics, their impact, and the value of the social economy is actively being conducted. Secondly, the 'co-occurrence word network' analysis demonstrated that research pertaining to social enterprises constitutes a pivotal topic within this field. The data analysis outcomes are of considerable significance, with the economic aspect of social enterprises and the purpose of enterprises also representing major research topics. Thirdly, eight themes were extracted through a comprehensive consideration of the implications of LDA-based topic extraction. The results demonstrated that social enterprises and social ventures are active in a multitude of fields, with a particular focus on the role and importance of various aspects, including consumer relations, support for individuals with disabilities, cultural access, urban regeneration, investment and responsibility, and partnerships. This demonstrates that social economy enterprises are playing a role in addressing social issues. The value of this study lies in its ability to draw inferences from the aforementioned research trends in the social economy domain through the utilisation of text mining analytical techniques. This study aspires to contribute to the formulation of prospective research directions in the field of social economy, with a foundation in the analysed research trends.