An Empirical Study of Sentiment-Enhanced Pre-Training for Aspect-Based Sentiment Analysis
Yice Zhang, Yifan Yang, Bin Liang, Shiwei Chen, Bing Qin, Ruifeng Xu · 2023
Aspect-Based Sentiment Analysis (ABSA) aims to recognize fine-grained opinions and sentiments of users, which is an important problem in sentiment analysis.Recent work has shown that Sentiment-enhanced Pre-Training (SPT) can substantially improve the performance of various ABSA tasks.However, there is currently a lack of comprehensive evaluation and fair comparison of existing SPT approaches.Therefore, this paper performs an empirical study to investigate the effectiveness of different SPT approaches.First, we develop an effective knowledge-mining method and leverage it to build a large-scale knowledgeannotated SPT corpus.Second, we systematically analyze the impact of integrating sentiment knowledge and other linguistic knowledge in pre-training.For each type of sentiment knowledge, we also examine and compare multiple integration methods.Finally, we conduct extensive experiments on a wide range of ABSA tasks to see how much SPT can facilitate the understanding of aspect-level sentiments. 1