Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates.

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Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates.

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2018 nî lūn-bûn

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2018年の論文

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2018年学术文章

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Predicting Depression From Lan ...... ok and Twitter Status Updates.

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Predicting Depression From Lan ...... ok and Twitter Status Updates.

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Predicting Depression From Lan ...... ok and Twitter Status Updates.

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Predicting Depression From Lan ...... ok and Twitter Status Updates.

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Predicting Depression From Lan ...... ok and Twitter Status Updates.

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Predicting Depression From Lan ...... ok and Twitter Status Updates.

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Predicting Depression From Lan ...... ok and Twitter Status Updates.

@en

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Elizabeth M Seabrook

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Personality, gender, and age in the language of social media: the open-vocabulary approach

Cognition and depression: current status and future directions

The PHQ-9: validity of a brief depression severity measure

A pilot evaluation of associations between displayed depression references on Facebook and self-reported depression using a clinical scale

Development of a Mobile Phone App to Support Self-Monitoring of Emotional Well-Being: A Mental Health Digital Innovation.

Standardization of the depression screener patient health questionnaire (PHQ-9) in the general population.

The Smartphone Psychology Manifesto.

Time-structured and net intraindividual variability: tools for examining the development of dynamic characteristics and processes.

Cross-sectional and longitudinal relations between affective instability and depression.

Inter-episode affective intensity and instability: predictors of depression and functional impairment in bipolar disorder.

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e168

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scholarly article

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10.2196/JMIR.9267

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2018-05-08T00:00:00Z

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29739736

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Facebook

Twitter

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5964306

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