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A Computational Diachronic Analysis of Gen Z Mental Health Discourse: A Large-scale Reddit Corpus Study from Pre- to Post-COVID

Generation Z’s mental health discourse has been uniquely shaped by digital saturation and the COVID-19 pandemic. This study introduces a large-scale corpus of Gen Z mental health discourse on Reddit, comprising over 3 million posts across 11 subreddits (2017–2025), identified through behavioral cross-posting between mental health and Gen Z-identified communities. Using a hybrid methodology that integrates statistical corpus linguistics with NLP techniques, we conduct diachronic keyness analysis, sentiment tracking, and topic modeling to examine lexical, syntactic, and semantic patterns across pre-, during-, and post-COVID periods. Our analysis reveals: (1) ritualized support exchanges more pronounced in Gen Z where highly negative self-disclosure functions as an authenticity signal; (2) a pandemic-induced reframing of existing mental health topics, particularly a rise in physical symptoms, followed by a sustained post-pandemic sentiment decline; and (3) a generational divergence where Gen Z favors abstract, existential concerns, unlike the pragmatic focus of non-Gen Z users. This study contributes a replicable approach for analyzing youth discourse and underscores the importance of culturally and linguistically informed digital mental health interventions, which can support Gen Z’s modes of expressing distress rather than pathologizing them.