Beyond Risk: Individual Mental Health Trajectories from Large-Scale Social Media Data

Johan Bollen, Marijn ten Thij, Lorenzo Lorenzo-Luaces, Lauren A. Rutter

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic


Depression and anxiety are now the 1st and 10th leading causes of disability worldwide. However, their variegated presentation and symptoms complicate efforts to develop a better understanding of the complex factors that shape the dynamics of their development within individuals. The development of personalized detection, diagnostics, and treatment options has been hindered by the lack of within-subject longitudinal observations at high temporal resolution and for large samples of individuals across the spectrum of internalizing disorders. Here, we discuss our efforts in the burgeoning field of precision mental health which leverages large-scale data of the behavioral, cognitive, emotional and social traces that billions of individuals leave behind when they interact with social media platforms. Our results point towards the possibility of modeling individualized mental health trajectories at population scale to identify high-precision targets for the detection, intervention, and mitigation of internalizing disorders.
Original languageEnglish
Title of host publicationEarly Detection of Mental Health Disorders by Social Media Monitoring: The First Five Years of the eRisk Project
EditorsFabio Crestani, David E. Losada, Javier Parapar
Place of PublicationCham
PublisherSpringer International Publishing
Number of pages23
ISBN (Print)978-3-031-04431-1
Publication statusPublished - 2022

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