# Mental Health via Writing

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/mental-health-via-writing/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the analysis of psychological language in social media, particularly related to emotional disclosure, mental health, and expressive writing. It involves the use of natural language processing and machine learning techniques to detect and understand patterns of depression, suicidal ideation, and other mental health indicators in online communication. |
| Domain | Social Sciences |
| Field | Psychology |
| OpenAlex ID | t12488 |
| Works | 113 |

## Topic papers all

Showing 15 of 113.

- [“Mental health literacy”: a survey of the public's ability to recognise mental disorders and their beliefs about the effectiveness of treatment](https://scholariq.org/papers/mental-health-literacy-a-survey-of-the-public-s-ability-to-recognise-mental/)
- [SANRA—a scale for the quality assessment of narrative review articles](https://scholariq.org/papers/sanra-a-scale-for-the-quality-assessment-of-narrative-review-articles/)
- [Mental health literacy](https://scholariq.org/papers/mental-health-literacy/)
- [Mental disorders and comorbidity in suicide](https://scholariq.org/papers/mental-disorders-and-comorbidity-in-suicide/)
- [Automatic personality assessment through social media language.](https://scholariq.org/papers/automatic-personality-assessment-through-social-media-language/)
- [Detecting depression and mental illness on social media: an integrative review](https://scholariq.org/papers/detecting-depression-and-mental-illness-on-social-media-an-integrative-review/)
- [Facebook language predicts depression in medical records](https://scholariq.org/papers/facebook-language-predicts-depression-in-medical-records/)
- [Prevalence of Depression in Patients With Mild Cognitive Impairment](https://scholariq.org/papers/prevalence-of-depression-in-patients-with-mild-cognitive-impairment/)
- [Psychological Language on Twitter Predicts County-Level Heart Disease Mortality](https://scholariq.org/papers/psychological-language-on-twitter-predicts-county-level-heart-disease-mortality/)
- [Automated assessment of psychiatric disorders using speech: A systematic review](https://scholariq.org/papers/automated-assessment-of-psychiatric-disorders-using-speech-a-systematic-review/)
- [Interapy: A controlled randomized trial of the standardized treatment of posttraumatic stress through the internet.](https://scholariq.org/papers/interapy-a-controlled-randomized-trial-of-the-standardized-treatment-of/)
- [Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation](https://scholariq.org/papers/self-supervised-multi-channel-hypergraph-convolutional-network-for-social/)
- [Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends](https://scholariq.org/papers/global-sentiments-surrounding-the-covid-19-pandemic-on-twitter-analysis-of/)
- [Problematic social media use and depressive symptoms among U.S. young adults: A nationally-representative study](https://scholariq.org/papers/problematic-social-media-use-and-depressive-symptoms-among-u-s-young-adults-a/)
- [Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis](https://scholariq.org/papers/equivalency-of-the-diagnostic-accuracy-of-the-phq-8-and-phq-9-a-systematic/)

## Topic primary papers

Showing 15 of 21.

- [Detecting depression and mental illness on social media: an integrative review](https://scholariq.org/papers/detecting-depression-and-mental-illness-on-social-media-an-integrative-review/)
- [Facebook language predicts depression in medical records](https://scholariq.org/papers/facebook-language-predicts-depression-in-medical-records/)
- [Psychological Language on Twitter Predicts County-Level Heart Disease Mortality](https://scholariq.org/papers/psychological-language-on-twitter-predicts-county-level-heart-disease-mortality/)
- [Automated assessment of psychiatric disorders using speech: A systematic review](https://scholariq.org/papers/automated-assessment-of-psychiatric-disorders-using-speech-a-systematic-review/)
- [Towards Assessing Changes in Degree of Depression through Facebook](https://scholariq.org/papers/towards-assessing-changes-in-degree-of-depression-through-facebook/)
- [Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications](https://scholariq.org/papers/suicidal-ideation-detection-a-review-of-machine-learning-methods-and/)
- [Deep Learning for Depression Detection from Textual Data](https://scholariq.org/papers/deep-learning-for-depression-detection-from-textual-data/)
- [Predicting mental health problems in adolescence using machine learning techniques](https://scholariq.org/papers/predicting-mental-health-problems-in-adolescence-using-machine-learning/)
- [How loneliness is talked about in social media during COVID-19 pandemic: Text mining of 4,492 Twitter feeds](https://scholariq.org/papers/how-loneliness-is-talked-about-in-social-media-during-covid-19-pandemic-text/)
- [Machine learning models to detect anxiety and depression through social media: A scoping review](https://scholariq.org/papers/machine-learning-models-to-detect-anxiety-and-depression-through-social-media-a/)
- [Speech as a Biomarker for Depression](https://scholariq.org/papers/speech-as-a-biomarker-for-depression/)
- [Natural language processing of clinical mental health notes may add predictive value to existing suicide risk models](https://scholariq.org/papers/natural-language-processing-of-clinical-mental-health-notes-may-add-predictive/)
- [Artificial Intelligence, Social Media and Depression. A New Concept of Health-Related Digital Autonomy](https://scholariq.org/papers/artificial-intelligence-social-media-and-depression-a-new-concept-of-health/)
- [Talking with text: Communication in therapist-led, live chat cancer support groups](https://scholariq.org/papers/talking-with-text-communication-in-therapist-led-live-chat-cancer-support-groups/)
- [Deep Learning-Based Detection of Depression and Suicidal Tendencies in Social Media Data with Feature Selection](https://scholariq.org/papers/deep-learning-based-detection-of-depression-and-suicidal-tendencies-in-social/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.