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With the social media engagement on the rise, the resulting data can be usedas a rich resource for analyzing and understanding different phenomena aroundus. A sentiment analysis system employs these data to find the attitude ofsocial media users towards certain entities in a given document. In this paperwe propose a sentiment analysis method for Persian text using ConvolutionalNeural Network (CNN), a feedforward Artificial Neural Network, that categorizesentences into two and five classes (considering their intensity) by applying alayer of convolution over input data through different filters. We evaluatedthe method on three different datasets of Persian social media texts using Areaunder Curve metric. The final results show the advantage of using CNN overearlier attempts at developing traditional machine learning methods for Persiantexts sentiment classification especially for short texts.

Convolutional Neural Networks for Sentiment Analysis in Persian Social Media