Research on the Classification of Policy Instruments Based on BERT Model

Abstract

Currently, policy instruments are classified mainly by means of manual encoding and checking, which is highly subjective and inefficient, which greatly hinders the development of policy research. The research tries to apply the automatic classification algorithm based on BERT (Bidirectional Encoder Representation from Transformer) to the policy instruments to improve the efficiency and accuracy of policy instruments classification. An entrepreneurship policy instrument classification model was established on the basis of the pretraining language model to realize the automatic classification of entrepreneurship policy instruments. The research showed that through optimization and improvement of the model, the F1 value was 0.86 on the test set, indicating a good classification effect; through the comparative experiment, it was further proved that the classification effect of this model was far superior to other three commonly used text classification models. The model greatly improves the efficiency and objectivity of policy instrument classification and provides a new idea for investigating entrepreneurship policies and more generalized policy instruments.