ArticleEntropy (Basel, Switzerland)2026
Characterizing Information Propagation in Social Media with Branching Processes.
Article in Entropy (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
Information propagation in social media has attracted the wide attention of scholars, with great progress made in empirical and modeling studies. Branching processes, extensively utilized in theoretical biology, are increasingly applied to model information diffusion dynamics. However, detailed and data-driven studies that implement this methodology remain rare. This study, utilizing empirical data, characterizes and models information diffusion in social media with branching processes. The reliability of the branching model is verified through the comparison of theoretical predictions, numerical simulations, and empirical results, and the model can replicate the key statistical characteristics observed in realistic cascades. The research results validate the applicability of branching processes in information diffusion, and contribute to the development of more elaborate, data-driven models of information spreading in complex real-world scenarios.
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