Sentiment analysis using convolutional neural networks with multi-task training and distant supervision on italian tweets

Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, Napoli, Italy, December 5-7, 2016(2016)

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摘要
In this paper, we propose a clas-sifier for predicting sentiments of Italian Twitter messages. This work builds upon a deep learning approach where we leverage large amounts of weakly labelled data to train a 2-layer convolutional neural network. To train our network we apply a form of multi-task training. Our system participated in the EvalItalia-2016 competition and outperformed all other approaches on the sentiment analysis task.
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