Coevolution spreading in complex networks.
The propagations of diseases, behaviors and information in real systems are rarely independent to each other, yet they are coevolving with strong interactions. To uncover the dynamical mechanisms, spatio-temporal evolving patterns and critical phenomena of networked coevolution spreading is extremely important, which provides some theoretical foundations for us to control epidemic spreading, to predict collective behaviors in social systems, and so on. The coevolution spreading dynamics in complex networks has thus attracted much attentions in many disciplines. In this review, we introduce recent progresses of coevolution spreading dynamics, emphasizing the contributions from the perspective of statistical mechanics and network science. The theoretical methods, critical phenomena, phase transitions, interacting mechanisms and effects of network topology for four representative types of coevolution spreading mechanisms, including the coevolution of biology contagions, social contagions, epidemic-awareness and epidemic-resources, are presented detailedly, and the challenges in this field as well as open issues for future studies are also discussed.
Publisher URL: http://arxiv.org/abs/1901.02125
Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.
Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.