@InProceedings{ghanem-EtAl:2019:S19-2,
  author    = {Ghanem, Bilal  and  Cignarella, Alessandra Teresa  and  Bosco, Cristina  and  Rosso, Paolo  and  Rangel Pardo, Francisco Manuel},
  title     = {UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post’s Nesting and Syntax Information for Rumor Stance Classification},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {1125--1131},
  abstract  = {In the present paper we describe the UPV-28-UNITO system’s submission to the RumorEval 2019 shared task. The approach we applied for addressing both the subtasks of the contest exploits both classical machine learning algorithms and word embeddings, and it is based on diverse groups of features: stylistic, lexical, emotional, sentiment, meta-structural and Twitter-based. A novel set of features that take advantage of the syntactic information in texts is moreover introduced in the paper.},
  url       = {http://www.aclweb.org/anthology/S19-2197}
}