Learn More
With the recent rise in popularity and scale of social media, a growing need exists for systems that can extract useful information from huge amounts of data. We address the issue of detecting influenza epidemics. First, the proposed system extracts influenza related tweets using Twitter API. Then, only tweets that mention actual influenza patients are(More)
Although web-based information extraction systems draw much attention, most of such systems assume that the web directly reflects the real world. For instance, Google flu trend, which is one of the-state-of-the-art influenza surveillance systems, relies on the basic idea that the amount of the influenza related search queries directly correlates with the(More)
Dictionary editing requires enormous time to discuss whether a word should be listed in a dictionary or not. So as to define a dictionary word, this study employs the number of word users as a novel metrics for selecting a dictionary word. In order to obtain the word user, we used about 0.25 billion tweets of approximately 100,000 people published for five(More)
  • 1