How followers build Instafame: an ego-network analysis of user-generated hashtags about influencers

Purpose While social media influencers (SMIs) are often theorized through self-branding and micro-celebrity lenses, this study reconceptualizes their identity formation as a networked and co-produced process. This study aims to investigate how follower-generated hashtag networks function as semantic infrastructures that shape influencer identities on Instagram. Design/methodology/approach This study adopts a mixed-method design, integrating ego-network analysis with qualitative content analysis. The analysis is based on 15,000 Instagram posts (5,000 posts for each of three mega-influencers) collected during late 2020. Ego-network analysis was used to identify the structural relationships among follower-generated hashtags, while qualitative content analysis of follower-generated captions examined the symbolic and cultural meanings embedded within these hashtag networks. Findings The results demonstrate that follower-generated content produces hierarchical hashtag networks that act as symbolic scaffolds for influencer brands. Eponymous hashtags are not merely metadata but serve as semantic hubs, linking influencers to genres, celebrities and relational personas (e.g. family, romance). This structure reveals followers’ active role in shaping cultural meaning through affective and symbolic labor. Practical implications Network analysis offers brands and influencers strategic tools for identifying influential hashtags and understanding audience-driven narratives. This approach enables more authentic engagement strategies by uncovering how followers frame influencer identities beyond curated self-presentation. Originality/value This study contributes to theory by bridging network theory with cultural branding to show that influencer identity is coconstructed within digital infrastructures of meaning. Hashtag networks reflect not just popularity but public symbolic expression, advancing theory on cultural production, platform dynamics and influencer–audience relationships.