Research on the Classification of New Energy Industry Policy Texts Based on BERT Model

Abstract

The existing means for classifying new energy industry policies are mainly based on the theory of policy instruments and manual encoding, which are highly subjective, less reproducible, and inefficient, especially when dealing with large-scale policy texts. Based on the theory of policy instrument, the research tried to apply the automatic classification model based on BERT to new energy industry policies to improve its classification efficiency and accuracy. A new energy industry policy classification model was established to train on policy texts and to compare the policy classification effects with the other two commonly used text classification models. The model comparison results show that the BERT model achieves higher precision, recall, and F1 score, indicating a better classification effect. Furthermore, adding topic sentences to training texts can effectively improve the classification effect of the BERT model. The policy classification results show that environmental policies are the most prevalent in new energy industry policies, while demand-side policy instruments are underutilized. Among the 11 types of subdivided policies, the application of goal planning policies is overflowing.