抄録
E-055
Predicting Onset and Outbreak of Influenza Like Diseases Using Social Media
○MuhammadAsif Khan・Masayuki Iwai・Kaoru Sezaki（The University of Tokyo）
Early detection of the onset and outbreak of influenza like contiguous diseases followed by timely intervention by authorities with rapid response can greatly reduce the damage caused by them. Unfortunately, till now actual data arrives in the hands of authorities with a lag time of ten days to two weeks. In this research we have used social media, namely Twitter, to predict the state of such disease outbreak by analyzing tweets made by the members of the community. We have used natural language processing techniques to identify and quantify health related tweets from normal tweets.