Emotional analysis of social media mental health based on deep learning

Xinyue Wang

doi:10.1117/12.2628221

18 February 2022 Emotional analysis of social media mental health based on deep learning

Xinyue Wang

Proceedings Volume 12162, International Conference on High Performance Computing and Communication (HPCCE 2021); 121621B (2022) https://doi.org/10.1117/12.2628221
Event: 2021 International Conference on High Performance Computing and Communication, 2021, Guangzhou, China

Abstract

Based on the expanding rigid demand for medical care, internet medical care is developing rapidly at an unprecedented speed. According to statistics of the World Health Organization in 2016, depression has become the second burden disease in China and is expected to rise to the first in the world by 2030. With the continuous popularization and development of the Internet and mobile networks, more and more social platforms appear in the public perspective. Researchers can get whether the subjects have depression tendency after emotional analysis of emotional texts from social media, which is of great significance for online medical treatment and depression screening. The method of text emotion analysis is often used in traditional fields by previous researchers, such as consumer emotion index, review analysis of film and television products, and it is rarely used in the field of mental health. In addition, the previous prediction of mental diseases focused on the use of traditional methods, such as conversation diagnosis, CT examination, painting diagnosis, etc., lacking the participation of the Internet. The main research content of this paper is the emotional analysis of social media on mental health related texts. After preprocessing and classifying the text data crawled from social media, this paper obtains the mental health emotion analysis data set, and proposes LSTM neural network based on the pre-training language model and a variety of traditional classification algorithms for this data set. The algorithm achieves good results on the data set proposed in this paper and realizes the prediction of depression tendency based on social media.

Citation Download Citation

Xinyue Wang "Emotional analysis of social media mental health based on deep learning", Proc. SPIE 12162, International Conference on High Performance Computing and Communication (HPCCE 2021), 121621B (18 February 2022); https://doi.org/10.1117/12.2628221

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KEYWORDS

Web 2.0 technologies

Analytical research

Data modeling

Internet

Classification systems

Neural networks

Heart

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