Dynamics of information diffusion and its applications on complex networks

Abstract

The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the information of effective transmission from heterogeneous individuals to various systems. Extensive research for information diffusion is introduced by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and empirical studies, unification and comparison of different theories and approaches are lacking, which impedes further advances. In this article, we review recent developments in information diffusion and discuss the major challenges. We compare and evaluate available models and algorithms to receptively investigate their physical roles and optimization designs. Potential impacts and future directions are discussed. We emphasize that information diffusion has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers.

Uncovering the popularity mechanisms for Facebook applications

“…Considering the fact that Apps' popularities are result of attracting more and more user attentions over time [34,35], we continue to conduct temporal analysis of growth characteristic for each App.…”

Coupling dynamics of epidemic spreading and information diffusion on complex networks

“…Interestingly, the empirical analysis also demonstrates that a multi-outbreak phenomenon emerges for both epidemic spreading [14,[57][58][59] and information diffusion [22] , in which there are several outbreaks during the dynamic process of epidemic spreading. Generally, there are many complicated factors that might contribute to this phenomenon, including seasonal influence, climate change, and incubation period, etc.…”

“…The majority of the aforementioned studies focused on epidemic spreading independently, ignoring the fact that information diffusion of the diseases themselves may also have significant impact on epidemic outbreaks [22] . For example, the outbreak of a contagious disease may lead to quick spreading of disease information, through either medias or friends.…”

Characteristics of Information Dissemination of Agricultural Safety Emergencies Based on Complex Network

“…A lot of models have been proposed to characterize this process, in which the most classical models are epidemic spreading models, such as the SIS model and SIR model, as a piece of information can be transmitted from one individual to another which is the similar pattern as the epidemic spreading [3,4]. Besides, perhaps the most commonly used models are the independent cascade model where the information flows over the network through cascade and the threshold model (including the linear threshold model and general threshold models) established based on the assumption that the neighbors play significant roles for the diffusion process [2,3,4]. Liu et al build the SAIR model based on well-known epidemic models to characterize super-spreading phenomenon in tweet information dissemination accompanied with super-spreaders [4].…”

“…Liu et al build the SAIR model based on well-known epidemic models to characterize super-spreading phenomenon in tweet information dissemination accompanied with super-spreaders [4]. Zhang et al compared and evaluated the available models and algorithms to respectively investigate their physical roles and optimization designs [3]. Liu et al offered a new insight to explore information dissemination from the perspective of statistical physics and constructed a weighted and directed complex network in which media are set as nodes, the dissemination relationships as edges and the dissemination times as the weight of the edges, and the result show that the dissemination network presents small world feature, which means relations among media are close and breaking news originating from any node can spread rapidly [5].…”