User Relationship Graph Construction and Key User Identification Based on User Profile Information

Identifying key users within social networks is critical for understanding the underlying network structure and the dynamics of information propagation. In conventional user identification approaches, user profile information is often underutilized, with emphasis placed predominantly on the structural connectivity of the network. To address this gap, this paper introduces a novel user identification framework that incorporates user profile data, leveraging the TSPR algorithm and the SIR model to effectively identify pivotal participants and core influencers within the network. By integrating users' interest topics and behavioral patterns, the proposed approach mitigates the limitations inherent in traditional structural-based methods, facilitating a more comprehensive and accurate representation of users' multidimensional influence. Experimental results validate the effectiveness and reliability of the model, demonstrating significant improvements in identifying key users and capturing their influence across multiple dimensions.