bet356(手机版)唯一官网登录入口

Online Social Networks Flu Trend Tracker - A Novel Sensory Approach to Predict Flu Trends

時間： 地點：九龍湖校區計算機樓三樓會議室

報告簡介：

Seasonal influenza epidemics cause several million cases of illnesses cases and about 250,000 to 500,000 deaths worldwide each year. Reducing the impact of these threats is of paramount importance for health authorities, and studies have shown that effective interventions can be taken to contain the epidemics, if early detection can be made. We introduce Social Network Enabled Flu Trends (SNEFT), a continuous data collection framework which monitors flu related messages on online social networks such as Twitter and Facebook and track the emergence and spread of an influenza. We show that text mining significantly enhances the correlation between online social network(OSN) data and the Influenza like Illness (ILI) rates provided by Centers for Disease Control and Prevention (CDC). For accurate prediction, we implemented an auto-regression with exogenous input (ARX) model which uses current OSN data and CDC ILI rates from previous weeks to predict current influenza statistics. Our results show that, while previous ILI data from the CDC offer a true (but delayed) assessment of a flu epidemic, OSN data provides a real-time assessment of the current epidemic condition and can be used to compensate for the lack of current ILI data. We observe that the OSN data is highly correlated with the ILI rates across different regions within USA and can be used to effectively improve the accuracy of our prediction. Therefore, OSN data can act as supplementary indicator to gauge influenza within a population and helps to discover flu trends ahead of CDC.

報告人簡介：

Dr. Benyuan Liu is a faculty member in the Department of Computer Science at the University of Massachusetts Lowell. He received his Ph.D. degree in computer science from the University of Massachusetts Amherst. Prior to that, he received his B.S. degree in physics from University of Science and Technology of China (USTC) and M.S. degree in physics from Yale University. Dr. Liu's main research interests are in the area of application, algorithm design and performance analysis of various computer networking technologies, and network and mobile security. His research has been published in premium computer networking conferen and journals. His research has been supported by the National Science Foundation (NSF), National Institutes of Health (NIH), DARPA, and Microsoft Research. He is a recipient of the NSF CAREER Award.

計算機網絡和信息集成教育部重點實驗室（bet356手机版唯一官网）