@InProceedings{pisarevskaya-litvinova-litvinova:2017:NLPIR,
  author    = {Pisarevskaya, Dina  and  Litvinova, Tatiana  and  Litvinova, Olga},
  title     = {Deception Detection for the Russian Language: Lexical and Syntactic Parameters},
  booktitle = {Proceedings of the 1st Workshop on Natural Language Processing and Information Retrieval associated with RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Inc.},
  pages     = {1--10},
  abstract  = {The field of automated deception detection in written texts is methodologically
	challenging. Different linguistic levels (lexics, syntax and semantics) are
	basically used for different  types of English texts to reveal if they are
	truthful or deceptive. Such parameters as POS tags and POS tags n-grams,
	punctuation marks, sentiment polarity of words, psycholinguistic features,
	fragments of syntaсtic structures are taken into consideration. The importance
	of different types of parameters was not compared for the Russian language
	before and should be investigated before moving to complex models and higher
	levels of linguistic processing. On the example of the Russian Deception Bank
	Corpus we estimate the impact of three groups of features (POS features
	including bigrams, sentiment and psycholinguistic features, syntax  and
	readability features) on the successful deception detection and find out that
	POS features can be used for binary text classification, but the results should
	be double-checked and, if possible, improved.},
  url       = {https://doi.org/10.26615/978-954-452-038-0_001}
}