Prompt-based System for Personality and Interpersonal Reactivity Prediction
This work addresses personality and reactivity prediction for social media analysis, but it is incremental as it applies existing methods to a shared task.
The authors tackled personality and interpersonal reactivity prediction by using a prompt-based learning method with a pre-trained language model, achieving results through data augmentation and model ensemble, though no concrete numbers are provided.
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.