Stance detection in Chinese microblogs with neural networks

Abstract

In this paper, we presents a stance detection system for NLPCC-ICCPOL 2016 share task 4. Our Stance Detection System can determinate whether the author of Weibo text is in favor of the given target, against the given target, or neither. We exploit LSTMs model and the average F score of our system is 56.56%. In contrast to the traditional target/aspect sentiment, the given target may not be preserved in Weibo text. We model the task as a classification problem, exploiting LSTMs as the basic part of classifier.