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If a piece of disinformation released from a terrorist organization propagates on Twitter and this adversarial campaign is detected after a while, how emergence responders can wisely choose a set of source users to start the counter campaign to minimize the disruptive influence of disinformation in a short time? This practical problem is challenging and… (More)
The detection of super-spreading events in infectious disease is crucial for public health emergency response. Here, heterogeneous and stochastic agent-based models explore the mechanism of super-spreading events.
BACKGROUND As the most popular video sharing website in the world, YouTube has the potential to reach and influence a huge audience. This study aims to gain a systematic understanding of what e-cigarette messages people are being exposed to on YouTube by assessing the quantity, portrayal and reach of e-cigarette videos. METHODS Researchers identified the… (More)
Discovering temporal patterns and changes in tobacco use has important practical implications in tobacco control. This paper presents one of the first comprehensive international studies of seasonal smoking patterns based on online searches performed. Using periodogram and cross-correlation, we find that smoking-related search behavior shows strong… (More)
Understanding the strategies to optimize/suppress information spreads under intense competition could provide important insights in a broad range of settings including viral marketing, emergency response and information system design. However, most of existing studies about competitive influence diffusion mainly focus on two-information competition… (More)
Important users are high-status vertices in social networks. They are everywhere in most fields of society and have big impact on those around them. Although a lot of effort has been made on identifying important users, the efficient methods still need to be developed, especially for the web users from Sina microblog, which is the most popular social… (More)