deepSA at SemEval-2017 Task 4: Interpolated Deep Neural Networks for Sentiment Analysis in Twitter
Tzu-Hsuan Yang, Tzu-Hsuan Tseng, Chia-Ping Chen · 2017
In this paper, we describe our system implementation for sentiment analysis in Twitter.This system combines two models based on deep neural networks, namely a convolutional neural network (CNN) and a long short-term memory (LSTM) recurrent neural network, through interpolation.Distributed representation of words as vectors are input to the system, and the output is a sentiment class.The neural network models are trained exclusively with the data sets provided by the organizers of SemEval-2017 Task 4 Subtask A. Overall, this system has achieved 0.618 for the average recall rate, 0.587 for the average F1 score, and 0.618 for accuracy.