@InProceedings{turcu-EtAl:2018:S18-1,
  author    = {Turcu, Ramona-Andreea  and  Amarandei, Sandra Maria  and  Fleșcan-Lovin-Arseni, Iuliana-Alexandra  and  Gifu, Daniela  and  Trandabat, Diana},
  title     = {EmoIntens Tracker at SemEval-2018 Task 1: Emotional Intensity Levels in \#Tweets},
  booktitle = {Proceedings of The 12th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {177--180},
  abstract  = {The „Affect in Tweets” task is centered on emotions categorization and evaluation matrix using multi-language tweets (English and Spanish). In this research, SemEval Affect dataset was preprocessed, categorized, and evaluated accordingly (precision, recall, and accuracy). The system described in this paper is based on the implementation of supervised machine learning (Naive Bayes, KNN and SVM), deep learning (NN Tensor Flow model), and decision trees algorithms.},
  url       = {http://www.aclweb.org/anthology/S18-1026}
}