SAG team results in the sentipolc challenge

The SAG team (Castellucci, Croce, Basili) participated to the Evalita Sentiment Analysis in Twitter in Italian challenge (Sentipolc 2016) with a Deep Learning architecture based on Convolutional Neural Networks.

The SAG systems, named unitor, achieved the first and the second position among 22 systems in the Subjectivity Detection task. In the Polarity Classification task SAG systems placed second and third among 28 systems.

Details about the systems and the results will be provided in the Evalita 2016 proceedings. In the meanwhile, a very similar architecture is described in “Injecting sentiment information in context-aware convolutional neural networks” (Croce et Al, 2016), available in the SocialNLP 2016 Proceedings.


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