The academic literature of social sciences records human civilization and
studies human social problems. With its large-scale growth, the ways to quickly
find existing research on relevant issues have become an urgent demand for
researchers. Previous studies, such as SciBERT, have shown that pre-training
using domain-specific texts can improve the performance of natural language
processing tasks. However, the pre-trained language model for social sciences
is not available so far. In light of this, the present research proposes a
pre-trained model based on the abstracts published in the Social Science
Citation Index (SSCI) journals. The models, which are available on GitHub
(this https URL), show excellent
performance on discipline classification, abstract structure-function
recognition, and named entity recognition tasks with the social sciences
literature.

本研究旨在通过基于 Social Science Citation Index (SSCI) 期刊发表的摘要的预训练模型来提高自然语言处理任务的性能，目前该模型已在 GitHub 上发布，并在学科分类、摘要结构 - 功能识别和命名实体识别任务中展现出了优秀的性能。