A Study on the Measurement and Dissemination Path of Cultural Industry Brand Influence Based on Social Network Analysis
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Abstract
The measurement and dissemination of cultural industry brand influence have become increasingly complex in digital media environments characterized by large-scale user interactions and rapid information diffusion. To overcome the limitations of traditional traffic-based evaluation metrics, this study proposes a social network analysis framework integrating network measurement and dynamic dissemination simulation. Directed weighted interaction networks are constructed from multi-platform user behavior data, and centrality metrics together with community detection algorithms are employed to identify key communication nodes and structural characteristics. Furthermore, dynamic dissemination path modeling is introduced to analyze information diffusion mechanisms and quantify brand influence evolution. Experimental results demonstrate that the proposed network-based indicators effectively capture both dissemination intensity and structural connectivity characteristics, while simulation outcomes closely match real-world communication processes. The study advances brand influence evaluation from isolated statistical indicators to network-oriented analysis and provides methodological references for information dissemination modeling, communication network analysis, and complex propagation systems.
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