@InProceedings{wohlgenannt-chernyak-ilvovsky:2016:LT4DH,
  author    = {Wohlgenannt, Gerhard  and  Chernyak, Ekaterina  and  Ilvovsky, Dmitry},
  title     = {Extracting Social Networks from Literary Text with Word Embedding Tools},
  booktitle = {Proceedings of the Workshop on Language Technology Resources and Tools for Digital Humanities (LT4DH)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {18--25},
  abstract  = {In this paper a social network is extracted from a literary text. The social
	network shows, how frequent the characters interact and how similar their
	social behavior is. Two types of similarity measures are used: the first
	applies co-occurrence statistics, while the second exploits cosine similarity
	on different types of word embedding vectors.
	The results are evaluated by a paid micro-task crowdsourcing survey. The
	experiments suggest that specific types of word embeddings like word2vec are
	well-suited for the task at hand and the specific circumstances of literary
	fiction text.},
  url       = {http://aclweb.org/anthology/W16-4004}
}