Prompt-based mental health screening from social media text
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917663542870016 |
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| author | Santos, Wesley Ramos dos Paraboni, Ivandre |
| author_facet | Santos, Wesley Ramos dos Paraboni, Ivandre |
| contents | This article presents a method for prompt-based mental health screening from a large and noisy dataset of social media text. Our method uses GPT 3.5. prompting to distinguish publications that may be more relevant to the task, and then uses a straightforward bag-of-words text classifier to predict actual user labels. Results are found to be on pair with a BERT mixture of experts classifier, and incurring only a fraction of its training costs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_05912 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Prompt-based mental health screening from social media text Santos, Wesley Ramos dos Paraboni, Ivandre Computation and Language This article presents a method for prompt-based mental health screening from a large and noisy dataset of social media text. Our method uses GPT 3.5. prompting to distinguish publications that may be more relevant to the task, and then uses a straightforward bag-of-words text classifier to predict actual user labels. Results are found to be on pair with a BERT mixture of experts classifier, and incurring only a fraction of its training costs. |
| title | Prompt-based mental health screening from social media text |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2401.05912 |