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This research article explores Instagram influencer networks using graph theory and machine learning techniques.With the growing impact of social media personalities, understanding their network structures and dynamics is crucial for effective marketing and brand engagement.We model Instagram's influencer ecosystem as a graph and apply several machine learning algorithms, including Node2Vec and Word2Vec, to perform tasks such as link prediction and community detection.Our analysis reveals significant patterns in influencer interactions and network connectivity, providing actionable insights into influencer behavior and the formation of online communities.These findings offer valuable implications for optimizing marketing strategies and enhancing brand collaborations within the social media landscape.
Kumari et al. (Wed,) studied this question.
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