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Information and epidemic propagation dynamics in complex networks is trulyimportant to discover and control terrorist attack and disease spread. How totrack, recognize and model such dynamics is a big challenge. With thepopularity of intellectualization and the rapid development of Internet ofThings (IoT), massive mobile data is automatically collected by millions ofwireless devices (e.g., smart phone and tablet). In this article, as a typicaluse case, the impact of network structure on epidemic propagation dynamics isinvestigated by using the mobile data collected from the smart phones carriedby the volunteers of Ebola outbreak areas. On this basis, we propose a model torecognize the dynamic structure of a network. Then, we introduce and discussthe open issues and future work for developing the proposed recognition model.

Reality Mining with Mobile Big Data: Understanding the Impact of Network Structure on Propagation Dynamics