@InProceedings{asakura-hangyo-komachi:2016:WNUT,
  author    = {Asakura, Yasunobu  and  Hangyo, Masatsugu  and  Komachi, Mamoru},
  title     = {Disaster Analysis using User-Generated Weather Report},
  booktitle = {Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {24--32},
  abstract  = {Information extraction from user-generated text has gained much attention with
	the growth of the Web.Disaster analysis using information from social media
	provides valuable, real-time, geolocation information for helping people caught
	up these in disasters. However, it is not convenient to analyze texts posted on
	social media because disaster keywords match any texts that contain words. For
	collecting posts about a disaster from social media, we need to develop a
	classifier to filter posts irrelevant to disasters. Moreover, because of the
	nature of social media, we can take advantage of posts that come with GPS
	information.
	However, a post does not always refer to an event occurring at the place where
	it has been posted.
	Therefore, we propose a new task of classifying whether a flood disaster
	occurred, in addition to predicting the geolocation of events from
	user-generated text. We report the annotation of the flood disaster corpus and
	develop a classifier to demonstrate the use of this corpus for disaster
	analysis.
	Author{2}{Affiliation}},
  url       = {http://aclweb.org/anthology/W16-3906}
}