Journal
SOFTWARE IMPACTS
Volume 12, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.simpa.2022.100296
Keywords
Pre-trained model; Personality prediction; Reactivity index prediction; Prompt-based learning
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This paper presents our proposed method for the PER and IRI shared tasks at WASSA 2022. We utilize prompt-based learning with a pre-trained language model to enhance the models, and employ data augmentation and model ensemble for improved results. Additionally, we provide an online software demonstration and the corresponding code for further research.
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.
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