A Review of Information Cascade Prediction Research: Concepts, Models, and Future Development Trends

Online social media has substantially accelerated the diffusion of information, with both online communication and digital transactions generating vast volumes of data on a daily basis. As a result, information cascade prediction has become a central research topic in social network analysis, yet a comprehensive overview of this field remains insufficient. To address this gap, a large body of relevant literature is collected and systematically examined to form an integrated understanding of information cascade research. First, the research background and significance of information cascades are presented to clarify their role in contemporary data-driven environments. Subsequently, the fundamental conceptual framework of information cascades is introduced, including definitions, classifications, commonly used datasets, and the evaluation indicators for assessing model performance. In parallel, different categories of information cascade modeling methods are compared and analyzed, allowing the advantages and limitations of each approach to be identified through comparative examination. Finally, the study offers an overall synthesis and highlights potential future directions for information cascade research, providing a structured reference for subsequent academic exploration and methodological development.