Title :
Detecting social signals of flu symptoms
Author :
Bumsuk Lee ; Jinyoung Yoon ; Seokjung Kim ; Byung-Yeon Hwang
Author_Institution :
Dept. of Comput. Sci. & Eng., Catholic Univ. of Korea, Daegu, South Korea
Abstract :
A cold and the flu are both respiratory illnesses and they are very common to us. Vaccination is the most effective way to prevent infection of the flu, but there is no way for a cold. Thus, the best strategy for individuals is to stay away from the flu or cold carriers and to wash their hands often. Early detection of flu epidemics and a quick response to that can minimize the impact of the flu. We observed tweets as social signals of flu symptoms to detect the flu epidemics in early stage. We compared a tweet corpus from nine cities in Korea to the weather factors, flu forecast, and Influenza-like Illness datasets. The results show the possibility of using social signals to detect epidemic diseases.
Keywords :
diseases; medical computing; social networking (online); Korea; cold carriers; cold infection prevent; flu carriers; flu epidemic disease detection; flu forecasting; flu impact minimization; flu infection prevention; flu symptoms; hand washing; influenza-like illness datasets; respiratory illnesses; social signal detection; tweet corpus; tweets; vaccination; weather factors; Biomedical monitoring; Monitoring; Steel; Event Detection; Flu Epidemics; Social Signals;
Conference_Titel :
Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2012 8th International Conference on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
978-1-4673-2740-4