Contributo in atti di convegno, 2016, ENG

Samskara minimal structural features for detecting subjectivity and polarity in Italian tweets

Russo I.; Monachini M.

Lari Lab, Istituto di Linguistica Computazionale Antonio Zampolli (ILC CNR), Italy

Sentiment analysis classification tasks strongly depend on the properties of the medium that is used to communicate opinionated content. There are some limitations in Twitter that force the user to exploit structural properties of this social network with features that have pragmatic and communicative functions. Samskara is a system that uses minimal structural features to classify Italian tweets as instantiations of a textual genre, obtaining good results for subjectivity classification, while polarity classification needs substantial improvements.

Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop EVALITA 2016, Napoli, 7/12/2016

Keywords

sentiment analysis, twitter

CNR authors

Russo Irene, Monachini Monica

CNR institutes

ILC – Istituto di linguistica computazionale "Antonio Zampolli"