ABSTRACT
This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic. COVID-19 brings a lot of challenges to government globally. Among the different strategies the most extensively adopted ones were lockdown, social distancing, and isolation among others. Most people with no mental illness history have been found with high risk of distress and psychological discomfort due to anxiety of being infected with the virus. Panic among people due to COVID-19 spread faster than the disease itself. The misinformation and excessive usage of social media in this pandemic era have adversely affected mental health across the world. Due to limited historical data, psychiatrists are finding it difficult to cure the mental illness of people resulting from the pandemic repercussion, fueled by social media forum. In this study the methodology used for data extraction is by considering the implications of social network platforms (such as Reddit) and levering the capabilities of a semi-supervised co-training technique-based use of Naïve Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) classifiers. The experimental results shows the efficacy of the proposed methodology to identify the mental illness level (such as anxiety, bipolar disorder, depression, PTSD, schizophrenia, and OCD) of those who are in anxious of being infected with this virus. We observed 1 to 5% improvement in the classification decision through the proposed method as compared to state-of-the-art classifiers.