Public mental health through social media in the post Covid-19 era

Bibliographic Data

ID22068811
AuthorsDeepika Sharma (0000-0002-6641-173X, Chitkara University), Jaiteg Singh (0000-0002-2370-9384, Chitkara University), Babar Shah (0000-0002-5090-4695, Zayed University), Farman Ali (0000-0002-9420-1588, Sungkyunkwan University, corresponding author), Ahmad Ali AlZubi (0000-0001-8477-8319, King Saud University), Mallak Ahmad AlZubi (Jordan University of Science and Technology)
Year2023
Volume11
Pages1323922-1323922
Publication date2023-12-11
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1323922
PMID38146469
OpenAlexW4389570964
LanguageEN
References cited46

Social media is a powerful communication tool and a reflection of our digital environment. Social media acted as an augmenter and influencer during and after COVID-19. Many of the people sharing social media posts were not actually aware of their mental health status. This situation warrants to automate the detection of mental disorders. This paper presents a methodology for the detection of mental disorders using micro facial expressions. Micro-expressions are momentary, involuntary facial expressions that can be indicative of deeper feelings and mental states. Nevertheless, manually detecting and interpreting micro-expressions can be rather challenging. A deep learning HybridMicroNet model, based on convolution neural networks, is proposed for emotion recognition from micro-expressions. Further, a case study for the detection of mental health has been undertaken. The findings demonstrated that the proposed model achieved a high accuracy when attempting to diagnose mental health disorders based on micro-expressions. The attained accuracy on the CASME dataset was 99.08%, whereas the accuracy that was achieved on SAMM dataset was 97.62%. Based on these findings, deep learning may prove to be an effective method for diagnosing mental health conditions by analyzing micro-expressions

Convolutional neural network · Deep learning · Facial expression · Feeling · Mental health · Psychiatry · Social distance · Social media · World Wide Web · Computer Science · Digital Mental Health Interventions · Emotion and Mood Recognition · Medicine · Mental Health via Writing · Psychology · Social Psychology · Artificial Intelligence

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Open DOIOpen Access