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This page is an AI-assisted Turkish summary of the study presented at the 26th World Congress of Psychiatry. The study belongs to the presenting authors; please refer to the original source when citing it.

Voices from the web: a comparative analysis of depression narratives across ethnic groups

Voices from the web: a comparative analysis of depression narratives across ethnic groups

In 441,000 online conversations about depression analyzed using artificial intelligence, Hispanic users expressed a markedly more negative emotional tone, greater helplessness, and more narratives focused on living with depression than non-Hispanic users.

The study aimed to compare how individuals from different ethnic backgrounds describe their experiences of depression outside clinical settings, focusing on Hispanic and non-Hispanic populations in the United States. A machine learning–powered social listening platform was used to analyze publicly available online conversations by self-identified individuals discussing depression over a 12-month period; searches were restricted to content originating from US internet protocol (IP) addresses, and duplicate posts were excluded. Natural language processing algorithms classified conversations by tone, dominant themes, and attitudes toward depression, and descriptive analyses were used to compare the two groups. A total of 441,000 unique conversations about depression were identified, of which 43,000 (9.8%) were from Hispanic individuals; approximately half of all discussions (48%) originated on topic-specific websites and 16% on social media platforms. Compared with non-Hispanic individuals, Hispanic individuals more frequently expressed a negative emotional tone (66% versus 39%), feelings of resignation or hopelessness (44% versus 30%), and content focused on living with depression (44% versus 25%), revealing distinct patterns of emotional expression and themes between the groups. According to the authors, these findings underscore the importance of culturally sensitive approaches to depression screening, communication, and treatment, and demonstrate the contribution of digital epidemiology to precision mental health and the reduction of disparities.

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