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Reduced semantic agency in language reliably indicates depressive experiences, particularly in postpartum contexts. This finding suggests agency-based linguistic markers could improve mental health screening tools.

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Area of Science:

  • Psycholinguistics
  • Computational Linguistics
  • Mental Health Research

Background:

  • Depression symptoms like anhedonia and avolition reflect a loss of personal agency.
  • Linguistic analysis has shown promise in detecting psychological states, including depression.

Purpose of the Study:

  • To investigate semantic agency as a linguistic marker for depressive experiences, specifically in the postpartum period.
  • To explore the relationship between semantic agency and established linguistic markers of depression.

Main Methods:

  • Analysis of Twitter (N=17,664) and Reddit (N=3033) data using machine learning topic detection, linguistic depression markers, and expert coding.
  • Quantitative analysis of semantic agency levels in posts related to postpartum experiences.

Main Results:

  • Reduced semantic agency was a consistent indicator of depressive features across both datasets.
  • Posts discussing postpartum depressive experiences showed significantly lower semantic agency.
  • Semantic agency was negatively correlated with established linguistic depression markers and expert-coded depressive experiences.

Conclusions:

  • Semantic agency is a potential novel marker for identifying depressive experiences, especially in postpartum contexts.
  • Agency-based linguistic markers could enhance the sensitivity of language-based mental health screening tools.
  • Further validation is needed to integrate these markers into clinical practice.