This paper describes our proposed method for the Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA) 2022 shared task on Personality Prediction (PER) and Reactivity Index Prediction (IRI). In this paper, we adopt the prompt-based learning method with the pre-trained language model to accomplish these tasks. Specifically, the prompt is designed to provide knowledge of the extra personalized information for enhancing the pre-trained model. Data augmentation and model ensemble are adopted for obtaining better results. Moreover, we also provided the online software demonstration and the codes of the software for further research.
翻译:本文介绍了我们为2022年主观、敏感和社会媒体分析(WASSA)个人预测和反应指数预测(IRI)共同任务计算方法讲习班所提议的方法。 在本文件中,我们采用了即时学习方法,采用预先培训的语言模式来完成这些任务,具体地说,即刻提供个人化的额外信息知识,以加强经过培训的模型。采用了数据扩充和模型组合,以取得更好的结果。此外,我们还提供了在线软件演示和软件代码,供进一步研究。