@InProceedings{chen-lin-ku:2016:COLINGDEMO,
  author    = {Chen, Wei-Fan  and  Lin, Fang-Yu  and  Ku, Lun-Wei},
  title     = {WordForce: Visualizing Controversial Words in Debates},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {273--277},
  abstract  = {This paper presents WordForce, a system powered by the state of the art neural
	network model to visualize the learned user-dependent word embeddings from each
	post according to the post content and its engaged users. It generates the
	scatter plots to show the force of a word, i.e., whether the semantics of word
	embeddings from posts of different stances are clearly separated from the
	aspect of this controversial word. In addition, WordForce provides the
	dispersion and the distance of word embeddings from posts of different stance
	groups, and proposes the most controversial words accordingly to show clues to
	what people argue about in a debate.},
  url       = {http://aclweb.org/anthology/C16-2057}
}