Do Ideas, Products, Messages, and Behaviors Really Spread Just Like Viruses?
Dr. Julia Poncela-Casasnovas
Departament d'Enginyeria Informàtica i Matemàtiques (Computer Science & Mathematics)
Universitat Rovira i Virgili
Refreshments will be served at 1:15 PM
Adoption of innovations, whether new ideas, technologies, or products, is crucially important in knowledge societies. Studies of adoption of innovations have generally focused on products with little societal impact (such as online apps) and, even if large-scale and real-world based, on heterogeneous populations. These limitations have so far hindered the development and testing of a mechanistic understanding of the adoption process. In this work, we experimentally study the adoption by critical care physicians of a medical innovation that complements current protocols for the diagnosis of life-threatening bacterial infections. We show through computational modeling of the experiment that infection spreading models – which have been formalized as generalized contagion processes – are not consistent with the experimental data. Instead, we find that a “persuasion” model inspired by opinion models is better able to reproduce the empirical data, providing insight into the mechanism of innovation adoption within this homogeneous population of highly-trained professionals. Using our model, we also propose an intervention scheme and show its possible impact on increasing the rate and robustness of innovation adoption in the real-world.
Dr. Julia Poncela-Casasnovas obtained her PhD in Physics at University of Zaragoza (Spain). Her dissertation was on Evolutionary Game Theory on Complex Networks, where she analyzed the interface between cooperative dynamics and the underlying structure of a given population. Her current research interests are in Complex Systems and big data in general, and more specifically, the study of different processes on top of complex topologies, such as social networks, using computer simulations and statistical analysis. Dr. Poncela-Casasnovas joined the Amaral Lab at Northwestern University as a postdoc for three and a half years, where she worked on analyzing social systems using computational and statistical methods. One project was about understanding the way ideas propagate within a professional network. Another one was a study of an online community for people that want to control their weight, where she worked to understand the correlations between network topology and individual’s behaviors. She recently moved back to Spain to work with Dr. Alex Arenas on multiplex networks (or multilayered networks). She is also currently starting new collaborations to apply network analysis tools to health and social problems and serving on the advisory board for the FIU Project, “Network Analysis of Student Retention and Persistence.”