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11 October 2023 Big five personality prediction based on pre-training language model and sentiment knowledge base
Hao Lin, Xiaolei Li
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Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128004I (2023) https://doi.org/10.1117/12.3004082
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China
Abstract
Machine learning-based personality prediction methods have become the mainstream prediction method. But existing Big Five personality prediction methods based on user-generated text rely too much on pre-trained language models to ignore the sentiment information. To tackle these issues, we propose a novel Big Five personality prediction method based on pre-trained language models and SenticNet6, which is a new sentiment knowledge base. The correlation analysis and ablation experiment shows that SenticNet6 can be used for Big Five personality prediction tasks. The experiment results indicate that our proposed method improves the state-of-art results for each Big Five personality trait by 9.89%, 9.39%, 2.99%, 3.01%, and 4.28% on Essays dataset, respectively.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Hao Lin and Xiaolei Li "Big five personality prediction based on pre-training language model and sentiment knowledge base", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128004I (11 October 2023); https://doi.org/10.1117/12.3004082
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KEYWORDS
Data modeling
Feature extraction
Data fusion
Machine learning
Neural networks
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