Developing and middle-income countries increasingly emphasize higher education and entrepreneurship in their long-term development strategy. Thus, our work focuses on the influence of higher education institutions (HEIs) on startup ecosystems in Brazil, an emerging economy. As traditional data to perform this type of study, such as surveys, are challenging to get, we propose an alternative approach. Given the growing capability of social media databases such as Crunchbase and LinkedIn to provide startup and individual-level data, we draw on computational methods to mine data for social network analysis. Our approach enables different types of analysis. First, we describe regional variability in entrepreneurial network characteristics. Then we examine the influence of elite HEIs in economic hubs on entrepreneur networks. Second, we investigate the influence of the academic trajectories of startup founders, including their courses of study and HEIs of origin, on the fundraising capacity of startups. We find that HEI quality and the maturity of the ecosystem influence startup success. We also observe that elite HEIs have a powerful influence on local entrepreneur ecosystems. Surprisingly, while the most nationally prestigious HEIs in the South and Southeast have the longest geographical reach, their network influence remains local. Our approach can be helpful, especially in countries with limited studies of the interaction between startups and institutional factors supporting them.