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The Internet has arrived in China, the most populous nation in the world, at a rapid rate. To account for the adoption and use of the Internet by Chinese audiences, the current study develops a theoretical framework that centers on three key independent variables in the diffusion process: perceptions (i.e., perceived characteristics of the Internet or PCI), motivations (perceived need for the Internet or PNI), and social context (perceived popularity of the Internet or PPI). In addition, adoption is conceptualized as involving four categories that are mutually exclusive at a given time but interchangeable over time. This classification enables investigation of discontinuance. The current study also examines reinvention by integrating use into diffusion process. Data from a probability survey of 2,500 residents in Beijing and Guangzhou in 2000 largely support the hypotheses of the model. The study illustrates the importance and benefits of a theory-driven approach to new media research.

a b s t r a c tThe interaction between disease and disease information on complex networks has facilitated an interdisciplinary research area. When a disease begins to spread in the population, the corresponding information would also be transmitted among individuals, which in turn influence the spreading pattern of the disease. In this paper, firstly, we analyze the propagation of two representative diseases ( H7N9 and Dengue fever ) in the real-world population and their corresponding information on Internet, suggesting the high correlation of the two-type dynamical processes. Secondly, inspired by empirical analyses, we propose a nonlinear model to further interpret the coupling effect based on the SIS (Susceptible-Infected-Susceptible) model. Both simulation results and theoretical analysis show that a high prevalence of epidemic will lead to a slow information decay, consequently resulting in a high infected level, which shall in turn prevent the epidemic spreading. Finally, further theoretical analysis demonstrates that a multi-outbreak phenomenon emerges via the effect of coupling dynamics, which finds good agreement with empirical results. This work may shed light on the in-depth understanding of the interplay between the dynamics of epidemic spreading and information diffusion.

Classic agenda-setting studies implied a zero-sum process, in which issues compete for media and public attention. Recent time series analyses on single issues have disregarded this central assumption. Evidence from a variety of sources was cited to illustrate that agenda-setting is a zero-sum game, due to the limited carrying capacity of the public agenda. A mathematical model was proposed to incorporate the strengths of both the classic approach and the time series technique. The model was tested with data on three recent issues. Results reveal both mutual competition and one-way attraction among issues.

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