Journal
NATURE HUMAN BEHAVIOUR
Volume 5, Issue 4, Pages 458-466Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41562-021-01050-7
Keywords
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Funding
- NSF [SMA/SME1636636]
- IU's Office of the Vice President for Research
- Urban Mental Health institute at the University of Amsterdam
- Wageningen University and Research
- ISI Foundation
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Individuals with self-reported diagnosis of depression exhibit higher levels of distorted thinking in their social media language, which may provide insights for identifying depression. The expression of distorted nature in tweets cannot be solely attributed to the presence of specific topics, sentiment, or first-person pronouns.
Depression is a leading cause of disability worldwide, but is often underdiagnosed and undertreated. Cognitive behavioural therapy holds that individuals with depression exhibit distorted modes of thinking, that is, cognitive distortions, that can negatively affect their emotions and motivation. Here, we show that the language of individuals with a self-reported diagnosis of depression on social media is characterized by higher levels of distorted thinking compared with a random sample. This effect is specific to the distorted nature of the expression and cannot be explained by the presence of specific topics, sentiment or first-person pronouns. This study identifies online language patterns that are indicative of depression-related distorted thinking. We caution that any future applications of this research should carefully consider ethical and data privacy issues. Cognitive distortions have a central role in the development of depression. Here, the authors examine the tweets of thousands of individuals who report a diagnosis of depression, revealing significantly higher levels of distortions compared with a control group of Twitter users.
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