8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing

Research Article

Detecting Social Signals of Flu Symptoms

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2012.250355,
        author={Bumsuk Lee and Jinyoung Yoon and Seokjung Kim and Byung-Yeon Hwang},
        title={Detecting Social Signals of Flu Symptoms},
        proceedings={8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing},
        publisher={IEEE},
        proceedings_a={COLLABORATECOM},
        year={2012},
        month={12},
        keywords={social signals flu epidemics event detection},
        doi={10.4108/icst.collaboratecom.2012.250355}
    }
    
  • Bumsuk Lee
    Jinyoung Yoon
    Seokjung Kim
    Byung-Yeon Hwang
    Year: 2012
    Detecting Social Signals of Flu Symptoms
    COLLABORATECOM
    ICST
    DOI: 10.4108/icst.collaboratecom.2012.250355
Bumsuk Lee1, Jinyoung Yoon1, Seokjung Kim1, Byung-Yeon Hwang1,*
  • 1: The Catholic University of Korea
*Contact email: byhwang@catholic.ac.kr

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.