What’s on URA activities
Interface between Social Science and Engineering2014.06.12
Quantitative Analysis of Diffusion Process
Professor Yasufumi Saruwatari, Faculty of Business Sciences
7 (7 faculty members, 0 postdoctoral fellows, none from other organizations)
Social system, operations research, marketing, information system, finance
It is known that our modern society is network-structured where every member has a strong relationship with others both socially and economically. Once an incident occurs, it is considered no one is free from its effects. For example, as most people may remember, the 2009 pandemic of a new strain of influenza affected not only people living in the vicinity of the source of the outbreak, but also everyone’s daily lives. Our information is instantly conveyed to others in the world by interactions. The research unit “Quantitative Analysis of Diffusion Process” is involved in the modeling of such a system.
Surveys of social trends to examine the control of information propagation
The research unit aims to clarify the process of the propagation of information through various simulations. For example, our previous studies derived the model, by employing the aviation network, of the spread of A/H1N1 across the U.S.A. following its outbreak in Mexico. As the timing and origin (Mexico City) of the outbreak had already been determined, by using the aviation data and the time-series data published by the WHO (Figure 1), our model identified the transmission route (Figure 2) consistently. The modeling of such a route allows us to develop methods to control the propagation of information.
The essence of information propagation in the fields of marketing, computer networks, and finance
In the fields of marketing, information/communication networks, and stock exchanges/currency transactions, information itself may sometimes create value. Therefore, it has become increasingly important to assess information in modern society. Our research unit aims to help people handle social networks in a more realistic manner beyond the realm of existing network science, and predict the handling of networks based on background information and responses from the recipients of information. We also aim to identify mathematical models to determine controllable variables, and apply them to future research.
● Analyses of the structures of health care networks and mechanisms of their reconstruction and expansion, part of the “quantitative analysis of diffusion process”, while promoting collaboration with health care institutions
● Planning and implementation of a symposium: “An analysis of the mechanism of information propagation”
(Interviewed on May 15, 2013)