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Revisiting the Semantic Severity of Anxiety and Depression: Computational Linguistic Study of Normalization and Pathologization

Revisiting the Semantic Severity of Anxiety and Depression: Computational Linguistic Study of Normalization and Pathologization

First, we trained a Continuous Bag of Words word2vec model on the entire corpus using the word2vec package in R (R Foundation for Statistical Computing) [27]. Next, we created a mental health vector by averaging the vectors of words strongly associated with mental health (eg, therapy, psychiatry, and diagnosis; see Multimedia Appendix 1 for details). This vector was used as a reference point for identifying mental health–related language.

Vojtech Pisl, Ana-Maria Bucur, Ioana R Podina

J Med Internet Res 2025;27:e73950