@InProceedings{kamijo-nasukawa-kitamura:2016:PEOPLES,
  author    = {Kamijo, Koichi  and  Nasukawa, Tetsuya  and  Kitamura, Hideya},
  title     = {Personality Estimation from Japanese Text},
  booktitle = {Proceedings of the Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {101--109},
  abstract  = {We created a model to estimate personality trait from authors' text written in
	Japanese and measured its performance by conducting surveys and analyzing the
	Twitter data of 1,630 users. We used the Big Five personality traits for
	personality trait estimation. Our approach is a combination of category- and
	Word2Vec-based approaches. For the category-based element, we added several
	unique Japanese categories along with the ones regularly used in the English
	model, and for the Word2Vec-based element, we used a model called GloVe. We
	found that some of the newly added categories have a stronger correlation with
	personality traits than other categories do and that the combination of the
	category- and Word2Vec-based approaches improves the accuracy of the
	personality trait estimation compared with the case of using just one of them.},
  url       = {http://aclweb.org/anthology/W16-4311}
}