Contributors: Universitat Pompeu Fabra Barcelona (UPF); Web-Instrumented Man-Machine Interactions, Communities and Semantics (WIMMICS); Inria Sophia Antipolis - Méditerranée (CRISAM); Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS); Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S); Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S); Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA); Università degli Studi di Roma Tor Vergata Roma, Italia = University of Rome Tor Vergata Rome, Italy = Université de Rome Tor Vergata Rome, Italie; University of Groningen Groningen; Dipartimento di Informatica Bari; Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA); Università degli studi di Torino = University of Turin (UNITO)
نبذة مختصرة : International audience ; English. The SENTIment POLarity Classification Task 2016 (SENTIPOLC), is a rerun of the shared task on sentiment classification at the message level on Italian tweets proposed for the first time in 2014 for the Evalita evaluation campaign. It includes three subtasks: subjectivity classification , polarity classification, and irony detection. In 2016 SENTIPOLC has been again the most participated EVALITA task with a total of 57 submitted runs from 13 different teams. We present the datasets – which includes an enriched annotation scheme for dealing with the impact on polarity of a figurative use of language – the evaluation methodology, and discuss results and participating systems. ; Descriviamo modalità e risul-tati della seconda edizione della campagna di valutazione di sistemi di sentiment analysis (SENTIment POLarity Classification Task), proposta nel contesto di " EVALITA 2016: Evaluation of NLP and Speech Tools for Italian ". In SENTIPOLCè SENTIPOLC`SENTIPOLCè stata valutata la capacità dei sistemi di riconoscere diversi aspetti del sentiment espresso nei messaggi Twitter in lingua italiana, con un'articolazione in tre sotto-task: subjectivity classification, polarity classification e irony detection. La cam-pagna ha suscitato nuovamente grande interesse, con un totale di 57 run inviati da 13 gruppi di partecipanti.
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