Identifying Localized Entrepreneurial Projects Through Semantic Social Network Analysis

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