Social Behavior and Mental Health: A Snapshot Survey under COVID-19 Pandemic

Abstract

Online social media provides a channel for monitoring people's social behaviors and their mental distress. Due to the restrictions imposed by COVID-19 people are increasingly using online social networks to express their feelings. Consequently, there is a significant amount of diverse user-generated social media content. However, COVID-19 pandemic has changed the way we live, study, socialize and recreate and this has affected our well-being and mental health problems. There are growing researches that leverage online social media analysis to detect and assess user's mental status. In this paper, we survey the literature of social media analysis for mental disorders detection, with a special focus on the studies conducted in the context of COVID-19 during 2020-2021. Firstly, we classify the surveyed studies in terms of feature extraction types, varying from language usage patterns to aesthetic preferences and online behaviors. Secondly, we explore detection methods used for mental disorders detection including machine learning and deep learning detection methods. Finally, we discuss the challenges of mental disorder detection using social media data, including the privacy and ethical concerns, as well as the technical challenges of scaling and deploying such systems at large scales, and discuss the learnt lessons over the last few years.

arXiv commentSubmitted to ACM Computing Surveys

References in corpus (7)

• Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter
• Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications
• A Text Classification Framework for Simple and Effective Early Depression Detection Over Social Media Streams
• Monitoring Depression Trend on Twitter during the COVID-19 Pandemic
• Detection and Classification of mental illnesses on social media using RoBERTa
• See and Read: Detecting Depression Symptoms in Higher Education Students Using Multimodal Social Media Data
• LonelyText: A Short Messaging Based Classification of Loneliness