Big Data & Entrepreneurship Identifying localized entrepreneurial projects through semantic Social Network Analysis

We propose a novel set of social network analysis, firm level and communication-based algo-rithms for mining the web to identify emerging entrepreneurial projects. These algorithms are implemented in a hybrid theoretical framework and tested in an on-line environment. The algo-rithms take account of: entrepreneurship as the relational capability for innovation and learning, the central role of computer-mediated communication, the construction of 'dynamic' semantic networks, and the temporal computation of network centrality measures. The temporal calcula-tion of betweenness of concepts allows us to extract and predict long-term trends for entrepre-neurial projects. We illustrate our approach by considering the nodes in a network (based on our previous empirical analysis) as localized potential entrepreneurs in the cultural and creative context, and the inherent Instagram community, and analyzing the semantic networks emerging from sharing hashtags.