| Autor: |
Qijian Zheng, Feng Liu, Shuya Xu, Jingyi Hu, Haixing Lu, Tingting Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Journal of Safety Science and Resilience, Vol 4, Iss 4, Pp 396-409 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2666-4496 |
| DOI: |
10.1016/j.jnlssr.2023.10.002 |
| Popis: |
The COVID-19 pandemic has had a profound impact on public mental health, leading to a surge in loneliness, depression, and anxiety. And these public psychological issues increasingly become a factor affecting social order. As researchers explore ways to address these issues, artificial intelligence (AI) has emerged as a powerful tool for understanding and supporting mental health. In this paper, we provide a thorough literature review on the emotions(EMO) of loneliness, depression, and anxiety (EMO-LDA) before and during the COVID-19 pandemic. Additionally, we evaluate the application of AI in EMO-LDA research from 2018 to 2023(AI-LDA) using Latent Dirichlet Allocation (LDA) topic modeling. Our analysis reveals a significant increase in the proportion of literature on EMO-LDA and AI-LDA before and during the COVID-19 pandemic. We also observe changes in research hotspots and trends in both field. Moreover, our results suggest that the collaborative research of EMO-LDA and AI-LDA is a promising direction for future research. In conclusion, our review highlights the urgent need for effective interventions to address the mental health challenges posed by the COVID-19 pandemic. Our findings suggest that the integration of AI in EMO-LDA research has the potential to provide new insights and solutions to support individuals facing loneliness, depression, and anxiety. And we hope that our study will inspire further research in this vital and revelant domin. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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