Big Data & Entrepreneurship: Identifying entrepreneurial projects through semantic social network analysis

Abstract. A novel set of social network analysis, firm level and communication based algorithms for mining the web (e.g. contemporary social media such as Instagram) to identify emerging entrepreneurial projects has been introduced. As known, measuring the temporal centrality of concepts in a relevant information sphere combined with a firm-level analytical perspective, can be applied to the analysis of social, cultural, and entrepreneurial schemas and mechanisms. In this context, regional policy and diagnostic analytics constitute an emerging and increasingly prominent research field which relies on trustworthy sources of big data to explore localized entrepreneurial discovery projects to improve the effectiveness of regional policy. In line with European Community regional policies and the recent focus on smart specialization strategies, we investigate the cultural and creative industry (C&Ci) and its participation in economic growth. The research adopts an inductive thinking process based on the logic of discovery as opposed to innovation, as suggested by Hirshleifer (1971). Examination of a localized entrepreneurial discovery project involves analysis of a transition path from an existing set of collective capabilities to the foundations of a new business. Our description of the localized entrepreneurial discovery project highlights the distinctiveness of community performative meanings in relation to the dynamic evolution and distribution of the 'sharing hashtag' network.