Mental disorder preventing by worry levels detection in social media using deep learning based on psycho-linguistic features: application on the COVID-19 lockdown period.
Journal:
Computers in biology and medicine
PMID:
40203736
Abstract
BACKGROUND: The COVID-19 pandemic has had a profound effect on the daily routines of individuals and has influenced various facets of society, including healthcare systems, economy, education, and more. With lockdown and social distancing measures, people turned to social media, such as Twitter, to stay connected and informed. It has allowed for the rapidly disseminating of information about the virus and its spread. As a result, public health concerns have become a growing problem in societies due to their high impact on individuals, healthcare systems, and organizations. Worry emotion is associated with anxiety, fear, and nervousness, which has increased among people during crises due to isolation and uncertainty. Therefore, identifying worry levels at early stages is crucial because they are a precursor to major related concerns in public health, including depression and self-harm.