<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lucia Passaro</style></author><author><style face="normal" font="default" size="100%">Pollacci, Laura</style></author><author><style face="normal" font="default" size="100%">Lenci, Alessandro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ItEM: A Vector Space Model to Bootstrap an Italian Emotive Lexicon</style></title><secondary-title><style face="normal" font="default" size="100%">Second Italian Conference on Computational Linguistics CLiC-it 2015</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><volume><style face="normal" font="default" size="100%">II</style></volume><isbn><style face="normal" font="default" size="100%">978-88-99200-62-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract><num-vols><style face="normal" font="default" size="100%">2</style></num-vols></record></records></xml>