[Colloq] PhD Thesis defense - Qian Zhang - April 16, 2pm, 166 WVH - Contagion and Ranking Processes in Complex Networks: the role of geography and interaction strength

[Jessica Biron]

PhD Thesis defense: Contagion and Ranking Processes in Complex Networks: the role of geography and interaction strength -- Qian Zhang 



Date: April 16 (Wednesday) 

Time: 2pm 

Location: WVH 166 



Abstract 

The recent global surge in the wide usage of pervasive technologies such as social media, smart phones and other GPS-enabled portable devices has provided abundant resources to understand dynamical processes on complex networks. At the same time, the easily accessible bibliographic data and geographical databases allow better understanding of scholarly networks and in charting the creation of knowledge globally. Moreover, the availability of large-scale human communication datasets presents new opportunities to study information dissemination and measure social interactions in real social systems. In this dissertation we focus on contagion and ranking processes on complex networks and explore the significant role that geography and interaction strength play in these processes. First, we investigate geospatial and temporal features of a publication dataset. We characterize the knowledge diffusion pattern between worldwide urban areas and its temporal evolution, and identify the key cities in the scientific research in Physics with a newly formulated ranking algorithm. Second, we propose a computational framework to detect and predict seasonal flu epidemics with geolocalized Tweet data for the United States in season 2013-2014. In the early period of a flu season, tweets containing information related with influenza-like illness (ILI) indicate the spatial distribution of possible initially infected individuals. With estimated initial infections from ILI-related tweets and the Global Epidemic and Mobility (GLEAM) model, we successfully predicted flu season starting time, peaking time and season intensity weeks early at both national and regional level. In the second part, we also explore the role interaction strength plays in contagion processes. For a human-to-human communication network, we develop a novel data-driven method to identify the importance of links in information cascading processes. This new link property characterizes the strength of ties and is able to capture both structural and diffusion roles of weak ties in the communication network. Through link removal percolation and data-driven SIR simulations, we show that the combined information of link importance and overlap provides the best way to identify weak links. Last but not least, we discover a phase transition between absorbing and active states of the classic Maki-Thompson rumor spreading model on random networks. The parameters of the contagion process as well as the network architecture determine whether the rumor will spread globally or whether it will be confined within a small neighborhood. 



Thesis Committee: 

- Alessandro Vespignani (advisor), College of Computer and Information Science & Department of Physics & Bouve' College of Health Science, Northeastern University 

- David Lazer , College of Computer and Information Science & Department of Political Science, Northeastern University 

- Alan Mislove , College of Computer and Information Science, Northeastern University 

- Marta C. González, Department of Civil and Environmental Engineering, MIT