@inproceedings{11568_766226,
 abstract = {In recent years computational linguistics has seen a rising interest in subjectivity, opinions, feelings and emotions. Even though great attention has been given to polarity recognition, the research in emotion detection has had to rely on small emotion resources. In this paper, we present a methodology to build emotive lexicons by jointly exploiting vector space models and human annotation, and we provide the first results of the evaluation with a crowdsourcing experiment.},
 address = {Torino},
 author = {Passaro, Lucia and Pollacci, Laura and Lenci, Alessandro},
 booktitle = {Proceedings of the Second Italian Conference on Computational Linguistics {{CLiC-it}} 2015},
 doi = {10.4000/books.aaccademia.1277},
 isbn = {978-88-99200-62-6},
 keywords = {Distributional semantics,Emotion detection,Emotive lexicon},
 pages = {215--220},
 publisher = {Academia University Press},
 title = {{{ItEM}}: A Vector Space Model to Bootstrap an Italian Emotive Lexicon},
 year = {2015}
}