Adapting Freely Available Resources to Build an Opinion Mining Pipeline in Portuguese

Patrik Lambert, Carlos Rodríguez-Penagos


Abstract
We present a complete UIMA-based pipeline for sentiment analysis in Portuguese news using freely available resources and a minimal set of manually annotated training data. We obtained good precision on binary classification but concluded that news feed is a challenging environment to detect the extent of opinionated text.
Anthology ID:
L14-1266
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2225–2228
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/293_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Patrik Lambert and Carlos Rodríguez-Penagos. 2014. Adapting Freely Available Resources to Build an Opinion Mining Pipeline in Portuguese. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2225–2228, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Adapting Freely Available Resources to Build an Opinion Mining Pipeline in Portuguese (Lambert & Rodríguez-Penagos, LREC 2014)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/293_Paper.pdf