Text Stance Detection Based on Deep Learning

Stance analysis refers to the usage of natural language processing and data mining technology to determine the stance tendency of a specific target topic in text. The current stance detection research faces the problem of the relationship between the topic target information and the stance text information being not fully tapped, which affects the text stance analysis task performance in social media. In view of this, based on the existing deep learning framework, combined with the topic target information in stance analysis, this study proposes a stance analysis model based on a convolutional neural network under the independent encoding of the topic target information and the condition encoding of the topic target information. The SemEval2016 English Dataset and the NLPCC2016 Chinese dataset are used herein separately to conduct the experiments. The experimental results show that the model is effective in the stance detection task of a specific topic target.