Depression Detection on Social Media: A Classification Framework and Research Challenges and Opportunities
Social media has become a safe space for discussing sensitive topics such as mental
disorders. Depression dominates mental disorders globally, and accordingly,
depression detection on social media has witnessed significant research advances.
This study aims to review the current state-of-the-art research methods and propose
a multidimensional framework to describe the current body of literature relating
to detecting depression on social media. A study methodology involved selecting
papers published between 2011 and 2023 that focused on detecting depression
on social media. Five digital libraries were used to find relevant papers: Google
Scholar, ACM digital library, PubMed, IEEE Xplore and ResearchGate. In selecting
literature, two fundamental elements were considered: identifying papers focusing
on depression detection and including papers involving social media use. In total, 50
papers were reviewed. Multiple dimensions were analyzed, including input features,
social media platforms, disorder and symptomatology, ground truth, and techniques.
Various types of input features were employed for depression detection, including
textual, visual, behavioral, temporal, demographic, and spatial features. Among
them, visual and spatial features have not been systematically reviewed to support
mental health researchers in depression detection. Despite depression’s fine-grained
disorders, most studies focus on general depression. Recent studies have shown that
social media data can be leveraged to identify depressive symptoms. Nevertheless,
further research is needed to address issues like depression validation, generalizability,
causes identification, and privacy and ethical considerations. An interdisciplinary
collaboration between mental health professionals and computer scientists may
help detect depression on social media more effectively.
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Domestic violence (DV) is widely recognized as a significant problem with detrimental impacts on the mental, physical, and socio-economic well-being of individuals, families, and the broader…
Social media has become a safe space for discussing sensitive topics such as mental
disorders. Depression dominates mental disorders globally, and accordingly,
depression detection…