@InProceedings{summa-resch-strube:2016:PEOPLES,
  author    = {Summa, Anja  and  Resch, Bernd  and  Strube, Michael},
  title     = {Microblog Emotion Classification by Computing Similarity in Text, Time, and Space},
  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     = {153--162},
  abstract  = {Most work in NLP analysing microblogs focuses on textual content thus
	neglecting temporal and spatial information. We present a new interdisciplinary
	method for emotion classification that combines linguistic, temporal, and
	spatial information into a single metric. We create a graph of labeled and
	unlabeled tweets that encodes the relations between neighboring tweets with
	respect to their emotion labels. Graph-based semi-supervised learning labels
	all tweets with an emotion.},
  url       = {http://aclweb.org/anthology/W16-4317}
}