@inproceedings{simeonova-2017-gradient,
    title = "Gradient Emotional Analysis",
    author = "Simeonova, Lilia",
    editor = "Kovatchev, Venelin  and
      Temnikova, Irina  and
      Gencheva, Pepa  and
      Kiprov, Yasen  and
      Nikolova, Ivelina",
    booktitle = "Proceedings of the Student Research Workshop Associated with {RANLP} 2017",
    month = sep,
    year = "2017",
    address = "Varna",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/R17-2006/",
    doi = "10.26615/issn.1314-9156.2017_006",
    pages = "41--45",
    abstract = {Over the past few years a lot of research has been done on sentiment analysis, however, the emotional analysis, being so subjective, is not a well examined dis-cipline. The main focus of this proposal is to categorize a given sentence in two dimensions - sentiment and arousal. For this purpose two techniques will be com-bined {--} Machine Learning approach and Lexicon-based approach. The first di-mension will give the sentiment value {--} positive versus negative. This will be re-solved by using Na{\"i}ve Bayes Classifier. The second and more interesting dimen-sion will determine the level of arousal. This will be achieved by evaluation of given a phrase or sentence based on lexi-con with affective ratings for 14 thousand English words.}
}