• DocumentCode
    593735
  • 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
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    544
  • Lastpage
    545
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • 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
  • Type

    conf

  • Filename
    6450948