Information Cascade Semantic Scholar An information (or informational) cascade occurs when a person observes the actions of others and then – despite possible contradictions in his her own private information signals – engages in the same acts. In this paper, we study the special role of diffusion sources in information diffusion and propose dssf, a diffusion source semantics fused cascade prediction framework to learn the latent semantics between users and diffusion sources.
Information Cascade Semantic Scholar This article presents a comprehensive review and categorization of information popularity prediction methods, from feature engineering and stochastic processes, through graph representation, to deep learning based approaches. We review the theory of information cascades and social learning, and discuss important themes, insights and applications of this literature as it has developed over the last thirty years. we also highlight open questions and promising directions for further theoretical and empirical exploration. In recent years, deep learning has been extensively applied in the domain of information cascade prediction. this paper primarily classifies, organizes, and summarizes the current research status and classic algorithms of information cascade prediction methods based on deep learning. In this paper, we analyze and quantify the structural patterns of information cascades and the interplay between structures, dynam ics and semantics. we collect the full scale information cascades generated during one week in tencent weibo to support our de tailed empirical studies.
Information Cascade Semantic Scholar In recent years, deep learning has been extensively applied in the domain of information cascade prediction. this paper primarily classifies, organizes, and summarizes the current research status and classic algorithms of information cascade prediction methods based on deep learning. In this paper, we analyze and quantify the structural patterns of information cascades and the interplay between structures, dynam ics and semantics. we collect the full scale information cascades generated during one week in tencent weibo to support our de tailed empirical studies. An information cascade occurs when individuals, having observed the actions and possibly payoffs of those ahead of them, take the same action regardless of their own information signals. Certain network topologies are particularly conducive to epidemics, while others decelerate and even prohibit rapid information spreading. here we review models that describe information cascades in complex networks, with an emphasis on the role and consequences of node centrality. The rapid expansion of online social networks has led to explosive growth of information cascades, necessitating effective prediction methods for both research and industry. This article presents a comprehensive review and categorization of information popularity prediction methods, from feature engineering and stochastic processes, through graph representation, to deep learning based approaches.
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