The paper describes our submission to the task on Sentiment Analysis on Twitter at SemEval 2016. The approach is based on a Deep Learning architecture using convolutional neural networks. The approach used only word embeddings as features. The submission used embeddings created from a corpus of news articles. We report on further experiments using embeddings built for a corpus of tweets as well as sentiment specific word embeddings obtained by distant supervision.
UniPI at SemEval-2016 Task 4: Convolutional Neural Networks for Sentiment Classificatio
ATTARDI, GIUSEPPE;
2016-01-01
Abstract
The paper describes our submission to the task on Sentiment Analysis on Twitter at SemEval 2016. The approach is based on a Deep Learning architecture using convolutional neural networks. The approach used only word embeddings as features. The submission used embeddings created from a corpus of news articles. We report on further experiments using embeddings built for a corpus of tweets as well as sentiment specific word embeddings obtained by distant supervision.File in questo prodotto:
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