Mapping entrepreneurial ecosystems through social media networks: A digital ecosystem approach

Entrepreneurial ecosystems (EEs) are being increasingly shaped by digital platforms that mediate interactions, structure visibility, and configure actor relationships. However, research on how these ecosystems operate within platform-native environments is limited. This study develops a novel methodological framework for mapping EEs using Instagram, a widely used but underexplored platform in entrepreneurship research. Drawing on actor-network theory (ANT) and social network analysis (SNA), this research analyzes a large-scale mentoring network comprising more than 27,000 Instagram pages in the Iranian startup ecosystem. Through expert-informed sampling, recursive data expansion, and multi-metric centrality analysis, the study identifies key structural patterns, actor roles, and community formations. Findings reveal a decentralized, multi-hub configuration in which hybrid actor types, including training anchors, content mentors, and community brokers, facilitate the flow of knowledge, legitimacy, and support. Rather than relying on centralized authority, influence is distributed across interconnected clusters, shaped by platform-specific affordances and algorithmic logics. While grounded in the Iranian context, the study generates generalizable insights into how social media platforms enable new forms of ecosystem organization, particularly in environments with institutional constraints. The contributions are threefold: theoretically, the study extends ANT to include digital platforms as active non-human actors within entrepreneurial systems; methodologically, it offers a replicable model for Instagram-based ecosystem mapping using open data and scalable network techniques; and empirically, it provides one of the first comprehensive digital ecosystem mappings in an emerging market context. The study offers implications for researchers, policymakers, and ecosystem builders seeking to understand or support entrepreneurial activity in digitally mediated environments.