Detecting influenza epidemics using Facebook public data

• Main Authors: Yao-Jen Liu, 柳姚仁
• Other Authors: Jau-Shien Chang
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/03403281062315533938

碩士 === 淡江大學 === 資訊管理學系碩士在職專班 === 103 === Every year, influenza causes hundreds of thousands deaths, resulting in serious health threat. Flu epidemic can be reduced through vaccination, if early detection of influenza spread trends, infection and deaths can be reduced. Taiwan currently no immediate flu surveillance system to monitor influenza-like illness system according to the emergency department statistics, there will be a week to a month''s delay time, for early warning of a pandemic, the timeliness is clearly insufficient. This study try to analyze the message from the social media to develop a set of high instantaneous influenza surveillance methods. Through a specific keyword combinations to analysis the public data related with flu on Facebook , compared CDC''s influenza statistical data through correlation analysis, we establishment an influenza surveillance model that based on social network. Experimental results show that this model predicts the weight data of the official statistics have significant correlation, confirming the feasibility of using social network to monitor flu. According to results of this research, the hope we can do for the government to monitor early indicators of flu activity, reduce flu risk.