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Semantic Agency Patterns Signal Depressive Experiences: Evidence From Postpartum Communication on Social Media.

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Title: Semantic Agency Patterns Signal Depressive Experiences: Evidence From Postpartum Communication on Social Media.
Authors: Witkowska, Marta (AUTHOR), Beneda, Marta (AUTHOR), Formanowicz, Magdalena (AUTHOR), Leszko, Magda (AUTHOR), Arslan, Selen (AUTHOR), Nikadon, Jan (AUTHOR), Kowalski, Joachim (AUTHOR), Erseghe, Tomaso (AUTHOR), Suitner, Caterina (AUTHOR), Stoyanov, Drozdstoy (AUTHOR)
Source: Depression & Anxiety (1091-4269). 2/8/2026, Vol. 2026, p1-23. 23p.
Subjects: Postpartum depression, Communication patterns, Text mining, Mental depression, Mental health screening, Machine learning, Psychological distress
Abstract: Depression‐related symptoms, such as loss of motivation and diminished interest in activities, correspond to loss of agency. Given recent evidence that agency (or its lack) can be reliably detected in language, we investigated how linguistic manifestations of agency relate to depressive experiences. In two studies, we explored whether semantic agency can serve as a novel marker of depressive experiences within the context of postpartum. We analyzed data from Twitter (Study 1, N = 17,664 tweets) and Reddit (Study 2, N = 3033 posts), using three complementary approaches: machine learning‐based topic detection, analysis of established linguistic markers of depression, and expert coding of depressive experiences. Across both studies, reduced semantic agency consistently emerged as a reliable indicator of depressive features. Posts discussing individuals' depressive experiences in the postpartum period exhibited lower levels of semantic agency; semantic agency within posts was negatively correlated with established linguistic markers of depression; and semantic agency was negatively linked to depressive experiences as coded by experts. These findings highlight the potential of semantic analysis for mental health applications, suggesting that agency‐based markers could enrich existing linguistic frameworks examining psychological distress. While this research is at an early stage, future validation could clarify whether such markers might enhance the sensitivity of language‐based screening tools for identifying individuals in need of mental health support. [ABSTRACT FROM AUTHOR]
Copyright of Depression & Anxiety (1091-4269) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Semantic Agency Patterns Signal Depressive Experiences: Evidence From Postpartum Communication on Social Media.
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  Data: <searchLink fieldCode="AR" term="%22Witkowska%2C+Marta%22">Witkowska, Marta</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Beneda%2C+Marta%22">Beneda, Marta</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Formanowicz%2C+Magdalena%22">Formanowicz, Magdalena</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Leszko%2C+Magda%22">Leszko, Magda</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Arslan%2C+Selen%22">Arslan, Selen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nikadon%2C+Jan%22">Nikadon, Jan</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kowalski%2C+Joachim%22">Kowalski, Joachim</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Erseghe%2C+Tomaso%22">Erseghe, Tomaso</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Suitner%2C+Caterina%22">Suitner, Caterina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Stoyanov%2C+Drozdstoy%22">Stoyanov, Drozdstoy</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Depression+%26+Anxiety+%281091-4269%29%22">Depression & Anxiety (1091-4269)</searchLink>. 2/8/2026, Vol. 2026, p1-23. 23p.
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  Data: <searchLink fieldCode="DE" term="%22Postpartum+depression%22">Postpartum depression</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+patterns%22">Communication patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Text+mining%22">Text mining</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+depression%22">Mental depression</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+health+screening%22">Mental health screening</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+distress%22">Psychological distress</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Depression‐related symptoms, such as loss of motivation and diminished interest in activities, correspond to loss of agency. Given recent evidence that agency (or its lack) can be reliably detected in language, we investigated how linguistic manifestations of agency relate to depressive experiences. In two studies, we explored whether semantic agency can serve as a novel marker of depressive experiences within the context of postpartum. We analyzed data from Twitter (Study 1, N = 17,664 tweets) and Reddit (Study 2, N = 3033 posts), using three complementary approaches: machine learning‐based topic detection, analysis of established linguistic markers of depression, and expert coding of depressive experiences. Across both studies, reduced semantic agency consistently emerged as a reliable indicator of depressive features. Posts discussing individuals' depressive experiences in the postpartum period exhibited lower levels of semantic agency; semantic agency within posts was negatively correlated with established linguistic markers of depression; and semantic agency was negatively linked to depressive experiences as coded by experts. These findings highlight the potential of semantic analysis for mental health applications, suggesting that agency‐based markers could enrich existing linguistic frameworks examining psychological distress. While this research is at an early stage, future validation could clarify whether such markers might enhance the sensitivity of language‐based screening tools for identifying individuals in need of mental health support. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Depression & Anxiety (1091-4269) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Communication patterns
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      – SubjectFull: Text mining
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      – SubjectFull: Mental depression
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      – SubjectFull: Mental health screening
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      – SubjectFull: Machine learning
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      – SubjectFull: Psychological distress
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      – TitleFull: Semantic Agency Patterns Signal Depressive Experiences: Evidence From Postpartum Communication on Social Media.
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              Text: 2/8/2026
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