YNU-HPCC at EmoInt-2017: Using a CNN-LSTM Model for Sentiment Intensity Prediction
You Zhang, Hang Yuan, Jin Wang, Xuejie Zhang · 2017
The sentiment analysis in this task aims to indicate the sentiment intensity of the four emotions (e.g.anger, fear, joy, and sadness) expressed in tweets.Compared to the polarity classification, such intensity prediction can provide more finegrained sentiment analysis.In this paper, we present a system that uses a convolutional neural network with long short-term memory (CNN-LSTM) model to complete the task.The CNN-LSTM model has two combined parts: CNN extracts local n-gram features within tweets and LST-M composes the features to capture longdistance dependency across tweets.Our submission ranked tenth among twenty two teams by average correlation scores on prediction intensity for all four types of emotions.