The information below is an evolving list of data sets (primarily from electronic/social media) that have been used to model mental-health phenomena. The raw data (with additional columns) can be found in data_sources.xlsx. If you are an author of any of these papers and feel that anything is misrepresented, please do not hesitate to reach out to me at kharrigian@jhu.edu.
For an overview of existing datasets, please consider reading our paper On the State of Social Media Data for Mental Health Research.
@inproceedings{harrigian2020state,
title={On the State of Social Media Data for Mental Health Research},
author={Harrigian, Keith and Aguirre, Carlos and Dredze, Mark},
booktitle={Proceedings of the 7th Workshop on Computational Linguistics and Clinical Psychology: Improving Access},
year={2021}
}
We hope this repository becomes the central knowledge base for researchers working at the intersection of NLP and mental health. However, we cannot achieve this goal without the support of the community.
You can view our backlog of literature that needs annotation here. To annotate one of these papers, or to annotate a paper we haven't yet identified, please begin by updating the backlog to note that you are taking responsibility for a paper's annotation. After, you can use our standardized annotation form to make a submission that will be reviewed and published within the main directory.
Last Update: 2021-06-18T16:34:43.198413
| Paper | Authors | Platform | Year | Target Outcomes |
|---|---|---|---|---|
| Inferring Social Media Users' Mental Health Status from Multimodal Information | Xu, Pérez-Rosas, Mihalcea | Flickr | 2020 | Mental Health (General) |
| Dilated LSTM with attention for Classification of Suicide Notes | Schoene, Lacy, Turner, Dethlefs | Death Row Last Statements, The Kernel, Tumblr | 2019 | Suicide, Imminent Death, Depression, Loneliness |
| Detection of Depression-related Posts in Reddit Social Media Forum | Tadesse, Lin, Xu, Yang | Reddit, Online Support Forums | 2019 | Depression |
| Protecting User Privacy and Rights in Academic Data-Sharing Partnerships: Principles from a pilot program at Crisis Text Line | Pisani, Kanuri, Filbin, Gallo, Gould, Lehmann, Levine, Marcotte, Pascal, Rousseau, Turner, Yen, Ranney | Crisis Text Line | 2019 | None |
| Mental Health Surveillance over Social Media with Digital Cohorts | Amir, Dredze, Ayers | 2019 | Depression, PTSD, Control | |
| CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts | Zirikly, Resnik, Uzuner, Hollingshead | 2019 | Suicidal Ideation | |
| Can acute suicidality be predicted by Instagram data? Results from qualitative and quantitative language analyses | Brown, Bendig, Fischer, Goldwich, Baumeister, Plener | 2019 | Non-suicidal Self-Injury | |
| Methodological Gaps in Predicting Mental Health States from Social Media: Triangulating Diagnostic Signals | Ernala, Birnbaum, Candan, Rizvi, Sterling, Kane, De Choudury | Twitter, Facebook | 2019 | Schizophrenia |
| Suicide Risk Assessment with Multi-level Dual-Context Language and BERT | Matero, Idnani, Son, Giorgi, Vu, Zamani, Limbachiya, Guntuku, Schwartz | 2019 | Suicidal Ideation | |
| Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention | Cao, Zhang, Feng, Wei, Wang, Li, He | Sina Weibo | 2019 | Suicidal Ideation |
| Automatic detection of eating disorder-related social media posts that could benefit from a mental health intervention | Yan, Fitzsimmons-Craft, Goodman, Krauss, Das, Cavazos-Rehg | 2019 | Eating Disorder | |
| Dreaddit: A Reddit Dataset for Stress Analysis in Social Media | Turcan, McKeown | 2019 | Stress | |
| Detecting Low Self-Esteem in Youths from Web Search Data | Zaman, Acharyya, Kautz, Silenzio | Google Search | 2019 | Self-esteem |
| BioInfo@UAVR at eRisk 2019: delving into social media texts for the early detection of mental and food disorders | Trifan, Luís Oliveira | 2019 | Anorexia, Depression | |
| Towards Augmenting Crisis Counselor Training by Improving Message Retrieval | DeMasi, Hearst, Recht | Synthetic Crisis Text Conversations | 2019 | None (Message Retrieval Task) |
| Multi-Task, Multi-Channel, Multi-Input Learning for Mental Illness Detection using Social Media Text | Kirinde Gamaarachichige, Inkpen | 2019 | Depression, PTSD, Control | |
| Adapting Deep Learning Methods for Mental Health Prediction on Social Media | Sekulic, Strube | 2019 | Depression | |
| User Dynamics in Mental Health Forums -- A Sentiment Analysis Perspective | Davcheva, Adam, Benlian | 3 Online mental-health forums | 2019 | Sentiment |
| Quick and (maybe not so) Easy Detection of Anorexia in Social Media Posts | Mohammadi, Amini, Kosseim | 2019 | Anorexia | |
| Using Topic Modeling to Detect and Describe Self-Injurious and Related Content on a Large- Scale Digital Platform | Franz, Nook, Mair, Nock | TeenHelp.org (Forum) | 2019 | Self-harm |
| A Framework for Early Detection of Antisocial Behavior on Twitter Using Natural Language Processing | Singh, Du, Zhang, Wang, Miao, Sianaki, Ulhaq | 2019 | Antisocial Behavior | |
| The Role of Features and Context on Suicide Ideation Detection | Wang, Wan, Paris | 2019 | Suicidal Ideation | |
| Identifying Depressive Users in Twitter Using Multimodal Analysis | Kang, Yoon, Yi Kim | 2019 | Depression | |
| Facebook language predicts depression in medical records | Eichstaedt, Smith, Merchant, Ungar, Crutchley, Pretoiuc-Pietro, Asch, Schwartz | 2018 | Depression | |
| A multilevel predictive model for detecting social network users with depression | Wongkoblap, Vadillo, Curcin | 2018 | Life Satisfaction, Depression | |
| Deep Learning for Depression Detection of Twitter Users | Husseini Orabi, Buddhitha, Husseini Orabi, Inkpen | 2018 | Depression | |
| Suicidal Trend Analysis of Twitter using Machine Learning and Neural Network | Shahreen, Subhani, Mahfuzur Rahman | 2018 | Suicidal Ideation | |
| Attention-based LSTM for Psychological Stress Detection from Spoken Language Using Distant Supervision | Winata, Pepijin Kampman, Fung | Twitter, Interview | 2018 | Stress |
| Exploring the utility of community-generated social media content for detecting depression: an analytical study on Instagram | Ricard, Marsch, Crosier, Hassanpour | 2018 | Depression | |
| Helping or hurting? predicting changes in users’ risk of self-harm through online community interactions | Soldaini, Walsh, Cohan, Han, Goharian | ReachOut (Online Forum) | 2018 | Change in Distress (Self-harm/Suicidal Ideation) |
| Identifying depression on reddit: The effect of training data | Pirina, I. & Çöltekin, Ç | Reddit, Online Support Forums | 2018 | Depression, Breast Cancer Support, Familiar Support, Relationship Support |
| Detecting suicidal ideation on forums: proof-of-concept study | Aladağ, Murderrisoglu, Akbas, Zahmacioglu, Bingol | 2018 | Suicidal Ideation | |
| Norms matter: contrasting social support around behavior change in online weight loss communities | Chancellor, Hu, De Choudhury | 2018 | Weight loss support vs. Eating-disorder encouragement | |
| Measuring the impact of anxiety on online social interactions | Dutta, Ma, De Choudhury | 2018 | Change in social interaction based on inferred anxiety | |
| Within and between-person differences in language used across anxiety support and neutral reddit communities | Ireland, Iserman | 2018 | Anxiety | |
| Hierarchical neural model with attention mechanisms for the classification of social media text related to mental health | Ive, Gkotis, Dutta, Stewart, Velupillai | 2018 | Borderline Personality Disorder, Bipolar Disorder, Schizophrenia, Anxiety, Depression, Self-harm, Suicidality, Addiction, Alcoholism, Opiates, Autism, and Control | |
| Measuring the latency of depression detection in social media. | Sadeque, Xu, Bethard | 2018 | Depression | |
| Cross-domain depression detection via harvesting social media | Shen, Jia, Shen Feng, He, Luan, Tang, Tiropanis, Chua, Hall | Twitter, Weibo | 2018 | Depression |
| Predicting depression from language-based emotion dynamics: longitudinal analysis of Facebook and twitter status updates | Seabrook, Kern, Fulcher, Rickard | Facebook, Twitter | 2018 | Depression |
| Accommodating Grief on Twitter: An Analysis of Expressions of Grief Among Gang Involved Youth on Twitter Using Qualitative Analysis and Natural Language Processing | Upton Patton, MacBeth, Schoenebeck, Shear, McKeown | 2018 | Grief, Aggression | |
| Automatic detection of cyberbullying in social media text | Van Hee, Jacobs, Emmery, Desmet, Lefever, Verhoeven, De Pauw, Daelemans, Hoste | AskFM | 2018 | Cyberbullying |
| Benchmarking Aggression Identification in Social Media | Kumar, Ojha, Malmasi, Zampieri | Facebook, Twitter | 2018 | Aggression |
| Natural Language Processing of Social Media as Screening for Suicide Risk | Coppersmith | 2018 | Suicide Attempt | |
| Not Just Depressed: Bipolar Disorder Prediction on Reddit | Sekulic ́, Gjurković, Šnajder | 2018 | Bipolar Disorder | |
| Predictive linguistic features of schizophrenia | Sarioglu Kayi, Diab, Pauselli, Compton, Coppersmith | Twitter, Essays | 2018 | Schizophrenia |
| "Let Me Tell You About Your Mental Health!" Contextualized Classification of Reddit Posts to DSM-5 for Web-based Intervention | Gaur, Kursuncu, Alambo, Sheth, Daniulaityle, Thirunaryan, Pathak | 2018 | Anxiety, Borderline Personality, Bipolar, Opiate Addiction, Self Hard, Addiction, Asperger's, Autism, Alcoholism, Opiate Usage, Schizophrenia, Self-hard, Suicidal Ideation | |
| Feature Attention Network: Interpretable Depression Detection from Social Media | Song, You, Chunk, Park | 2018 | Depression | |
| Overview of eRisk: Early Risk Prediction on the Internet | Losada, Crestani, Parapar | 2018 | Depression, Anorexia | |
| Text-based Detection and Understanding of Changes in Mental Health | Li, Mihalcea, Wilson | 2018 | Change in Mental Health Disorder Communication | |
| Can Text Messages Identify Suicide Risk in Real Time? A within-subjects pilot examination of temporally sensitive markers of suicide risk | Glenn, Nobles, Barners, Teachman | SMS | 2018 | Periods of Suicide Attempts, Suicidal Ideation, Depressive Episodes, Positive Mood |
| Detecting Linguistic Traces of Depression Topic-Restricted Text: Attending to Self-Stigmatized Depression with NLP | Wolohan, Hirgaga, Mukerjee, Sayyed | 2018 | Depression | |
| RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses | MacAvaney, Desmet, Cohan, Soldaini, Yates, Zirikly, Goharian | 2018 | Depression Diagnosis Date | |
| SMHD: A Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions | Cohan, Desmet, Yates, Soldaini, MacAvaney, Goharian | 2018 | ADHD, Anxiety, Autism, Bipolar Disorder, Depression, Eating Disorder, Obsessive Compulsive Disorder, PTSD, Schizophrenia | |
| Cross-cultural differences in language markers of depression online | Loveys, Torrez, Fine, Moriarty, Coppersmith | 7 Cups of Tea (Chat-based peer support platform) | 2018 | None |
| Detecting Comments Showing Risk for Suicide in YouTube | Gao, Cheng, Yu | YouTube | 2018 | Suicidal Ideation |
| Expert, Crowdsourced, and Machine Assessment of Suicide Risk via Online Postings | Shing, Nair, Zirikly, Friedenberg, Daumé III, Resnik | 2018 | Suicidal Ideation | |
| Identification of Imminent Suicide Risk Among Young Adults using Text Messages | Nobles, Glenn, Kowsari, Teachman, Barnes | SMS, emails, and call history, social media data (i.e., Twitter and Facebook), web browsing history | 2018 | Suicidal Ideation |
| #MyDepressionLooksLike: Examining Public Discourse About Depression on Twitter | Lachmar, Wittenborn, Bogen, McCauley | 2017 | Depression | |
| Multi-Task Learning for Mental Health using Social Media Text | Benton, Mitchell, Hovy | 2017 | Neuroatypicality, Suicide Attempt, Anxiety, Depression, Eating Disorder, Panic Attacks, Schizophrenia, Bipolar Disorder, PTSD | |
| Modeling Stress with Social Media Around Incidents of Gun Violence on College Campuses | Saha, De Choudhury | 2017 | Stress | |
| Detecting anxiety on Reddit | Hanwen Shen, Rudzicz | 2017 | Anxiety | |
| Assessing suicide risk and emotional distress in Chinese social media: a text mining and machine learning study | Cheng, Li, Kwok, Zhu, Yip | Sina Weibo | 2017 | Suicidal Ideation, Depression, Anxiety, and Stress |
| The Language of Social Support in Social Media and its Effect on Suicidal Ideation Risk | De Choudury, Kiciman | 2017 | Suicidal Ideation | |
| Detection of Suicide-Related Posts in Twitter Data Streams | Vioulès, Moulahi, Azé, Bringay | 2017 | Suicidal Ideation | |
| Characterization of mental health conditions in social media using Informed Deep Learning | Gkotsis, Oellrich, Velupillai, Liakata, Hubbard, Dobson, Dutta | 2017 | Borderline Personality Disorder, Bipolar Disorder, Schizophrenia, Anxiety, Depression, Self-harm, Suicidality, Addiction, Alcoholism, Opiates, Autism, and Control | |
| Detecting cognitive distortions through machine learning text analytics | Simms, Ramstedt, Rich, Richards, Martinez, Giraud-Carrier | Tumblr | 2017 | Cognitive Distortion |
| A collaborative approach to identifying social media markers of schizophrenia by employing machine learning and clinical appraisals | Birnbaum, Kiranmai Ernala, Rizvi, De Choudhury, Kane | 2017 | Schizophrenia | |
| Social Media Based Index of Mental Well-Being in College Campuses | Bagroy, Kumaraguru, De Choudhury | 2017 | 14 mental-health related subreddits + small set of control subreddits (e.g. r/AskReddit) | |
| Understanding and Discovering Deliberate Self-harm Content in Social Media | Wang, Tang, Li, Li, Wan, Mellina, O'Hare, Chang | Flickr | 2017 | Self-harm |
| Small but Mighty: Affective Micropatterns for Quantifying Mental Health from Social Media Language | Loveys, Crutchley, Wyatt, Coppersmith | 2017 | Suicide Attempt, Schizophrenia, Panic, Eating, Anxiety | |
| Detecting and Characterizing Eating-Disorder Communities on Social Media | Wang, Brede, Ianni, Mentzakis | 2017 | Eating Disorder | |
| Emotional and Linguistic Cues of Depression from Social Media | Vedula, Parthasarathy | 2017 | Depression | |
| Depression detection via harvesting social media: A multimodal dictionary learning solution | Shen, Jia, Feng, Zhang, Hu, Chua, Zhu | 2017 | Depression | |
| Identifying Depression on Twitter | Nadeem, Horn, Coppersmith, Sen | 2017 | Depression, PTSD, Control | |
| Inferring Mood Instability on Social Media by Leveraging Ecological Momentary Assessments | Saha, Chan, Barbaro, Abowd, De Choudhury | Twitter, Facebook, Ecological Momentary Assessments | 2017 | Mood Instability, Bipolar Disorder, Borderline Personality Disorder |
| Depression and Self-Harm Risk Assessment in Online Forums | Yates, Cohan, Goharian | 2017 | Depression | |
| Monitoring Tweets for Depression to Detect At-risk Users | Jamil | 2017 | Depression | |
| Gender and Cross-Cultural Differences in Social Media Disclosures of Mental Illness | De Choudury, Sharma, Logar, Eekhout, Cluasen Nielsen | 2017 | Suicidal Ideation | |
| Quantifying Mental Health from Social Media with Neural User Embeddings | Amir, Coppersmith, Carvalho, Silva, Wallace | 2017 | Depression, PTSD, Control | |
| Learning from various labeling strategies for suicide-related messages on social media: An experimental study | Liu, Chen, Homan, Silenzio | 2017 | Suicidal Risk | |
| Understanding Depressive Symptoms and Psychosocial Stressors on Twitter: A Corpus-Based Study | Mowery, Smith, Cheney, Stoddard, Coppersmith, Bryan, Conway | 2017 | Depression (Symptoms) | |
| Content Analysis of Depression-Related Tweets | Cavazos-Reh, Krauss, Sowles, Connolly, Rosasa, Bharadwaj, Bierut | 2017 | Feelings of Depression, Support for Depression, School or Work-related Pressures related to Depression, Substance use to deal with depression, self-hard or suicidal thoughts | |
| Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media | Hossein Yazdavar, Al-Olimat, Ebrahimi, Bajaj, Banerjee, Thirunarayan, Pathak, Sheth | 2017 | Depression | |
| Instagram photos reveal predictive markers of depression | Reece, Danforth | 2017 | Depression | |
| Predicting Multiple Risky Behaviors via Multimedia Content | Zhou, Zhang, Luo | 2017 | Depression, Drug Use, Alcohol Use, Sleep Disorder, Eating Disorder | |
| Triaging content severity in online mental health forums | Cohan, Young, Yates, Goharian | ReachOut (Online Forum) | 2017 | Self-harm/Suicidal Ideation |
| eRISK 2017: CLEF Lab on Early Risk Prediction on the Internet: Experimental Foundation | Losada, Crestani, Parapar | 2017 | Depression | |
| Validating machine learning algorithms for twitter data against established measures of suicidality | Braithwaite, Giraud-Carrier, West, Barnes, Lee Hanson | 2016 | Suicidality | |
| Quantifying and Predicting Mental Illness Severity in Online Pro-Eating Disorder Communities | Chancellor, Lin, Goodman, Zerwas, De Choudhury | 2016 | Eating Disorder | |
| What does social media say about your stress? | Lin, Jia, Nie, Shen, Chua | Sina Weibo | 2016 | Stress, Stress (Stressor and Stress Subject) |
| Natural Language Processing for Mental Health: Large Scale Discourse Analysis of Counseling Conversations | Althoff, Clark, Leskovec | Crisis Text Line | 2016 | Counseling Outcome |
| MIDAS: Mental illness detection and analysis via social media | Saravia, Chang, Jollet De Lorenzo, Chen | 2016 | Borderline Personality Disorder, Bipolar Disorder | |
| Discovering shifts to suicidal ideation from mental health content in social media | De Choudhury, Kiciman, Dredze, Coppersmith, Kumar | 2016 | Depression, Mental Health (General), Trauma, Bipolar, Borderline Personality, PTSD, Psychosis, Eating Disorders, Self Harm, Rape Survivors, Panic, Social Anxiety, Suicidal Ideation | |
| Towards Automatically Classifying Depressive Symptoms from Twitter Data for Population Health | Mowery, Park, Conway, Bryan | 2016 | Depressive Symptoms and Stressors Associated with Depression | |
| Recovery Amid Pro-Anorexia: Analysis of Recovery in Social Media | Chancellor, Mitra, De Choudhury | Tumblr | 2016 | Anorexia (Recovery) |
| The language of mental health problems in social media | Gkotis, Oellrich, Hubbard, Dobson, Liakata, Velupillai, Dutta | 2016 | Anxiety, Borderline Personality, Bipolar, Opiate Addiction, Self Hard, Addiction, Asperger's, Autism, Alcoholism, Opiate Usage, Schizophrenia, Self-hard, Suicidal Ideation | |
| Exploratory Analysis of Social Media Prior to a Suicide Attempt | Coppersmith, Ngo, Leary, Wood | 2016 | Suicide Attempt | |
| CLPsych 2016 Shared Task: Triaging Content in Online Peer Support Forums | Milne, Pink, Hachey, Calvo | ReachOut (Online Forum) | 2016 | Self-harm |
| Forecasting the Onset and Course of Mental Illness with Twitter Data | Reece, Reagan, Lix, Dodds, Danforth, Langer | 2016 | Depression, PTSD | |
| The role of personality, age, and gender in tweeting about mental illnesses | Preotiuc-Pietro, Eichstaedt, Park, Sap, Smith, Toblosky, Schwartz, Ungar | 2015 | Depression, PTSD | |
| From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses | Coppersmith, Dredze, Harman, Hollingshead | 2015 | ADHD, Anxiety, Bipolar Disorder, Borderline Personality Disorder, Depression, Eating, OCD, PTSD, Schizophrenia, Seasonal Affective Disorder | |
| Recognizing Depression From Twitter Activity | Tsugawa, Kikuchi, Kishino, Nakajimi, Itoh, Ohsaki | 2015 | Depression | |
| Detecting Suicidality on Twitter | O'Dea, Wan, Batterham, Calear, Paris, Christensen | 2015 | Suicidal Ideation | |
| CLPsych 2015 Shared Task: Depression and PTSD on Twitter | Coppersmith, Dredze, Harman, Hollingshead, Mitchell | 2015 | Depression, PTSD, Control | |
| Beyond LDA: exploring supervised topic modeling for depression-related language in Twitter | Resnik, Armstrong, Claudino, Nguyen, Nguyen, Boyd-Graber | Twitter, Essays | 2015 | Depression |
| Towards Developing an Annotation Scheme for Depressive Disorder Symptoms: A Preliminary Study using Twitter Data | Mowery, Bryan, Conway | 2015 | Major Depressive Disorder | |
| Topic Model for Identifying Suicidal Ideation in Chinese Microblog | Huang, Li, Zhang, Liu, Chiu, Zhu | Sina Weibo | 2015 | Suicidal Ideation |
| Mixed-Initiative Real-Time Topic Modeling & Visualization for Crisis Counseling | Dinakar, Chen, Lieverman, Picard, Fill-in | Crisis Text Line | 2015 | None |
| Teenagers’ stress detection based on time-sensitive microblog comment/response actions | Zhao, Jia, Feng | Tencent Weibo | 2015 | Stress |
| Anorexia on Tumblr: A Characterization Study on Anorexia | De Choudhury | Tumblr | 2015 | Anorexia (Recovery), Anorexia |
| Machine Classification and analysis of suicide-related communication on Twitter | Burnap, Colombo, Scourfield | 2015 | Suicidal Ideation | |
| Understanding and Fighting Bullying with Machine Learning | Junming Sui | 2015 | Cyberbullying | |
| Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides | Kumar, Dredze, Coppersmith, De Choudury | Reddit, Wikipedia | 2015 | Suicidal Ideation |
| Mining Twitter data to improve detection of schizophrenia | McManus, Mallory, Goldfelder, Haynes, Tatum | 2015 | Schizophrenia | |
| Quantifying the language of schizophrenia in social media | Mitchell, Hollingshead, Coppersmith | 2015 | Schizophrenia | |
| Identifying Chinese Microblog Users with High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model | Guan, Hao, Cheng, Yip, Zhu | Sina Weibo | 2015 | Suicidal Ideation |
| User-level psychological stress detection from social media using deep neural network | Lin, Jia, Guo, Xue, Li, Huang, Cai, Feng | Sina Weibo, Tencent Weibo, Twitter | 2014 | Stress |
| Tracking Suicide Risk Factors Through Twitter in the US | Jashinky, Burton, Hanson, West, Giraud-Carrier, Barnes, Argyle | 2014 | Suicidal Ideation | |
| Towards Assessing Changes in Degree of Depression through Facebook | Schwartz, Eichstaedt, Kern, Park, Sap, Stillwell, Kosinski, Ungar | 2014 | Continuous Depression Score | |
| Quantifying Mental Health Signals in Twitter | Coppersmith, Dredze, Harman | 2014 | Bipolar Disorder, Depression, PTSD, Seasonal Affective Disorder (SAD) | |
| Characterizing and Predicting Postpartum Depression from Shared Facebook Data | De Choudhury, Counts, Horvitz, Hoff | 2014 | Post Partum Depression | |
| Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users | Zhang, Huang, Liu, Chen, Zhu | Sina Weibo | 2014 | Suicidal Ideation |
| Measuring post traumatic stress disorder in Twitter | Coppersmith, Harman, Dredze | 2014 | PTSD | |
| Psychological stress detection from cross-media microblog data using deep sparse neural network | Lin, Jia, Guo, Xue, Li, Huang, Cai, Feng | Sina Weibo | 2014 | Stress |
| Twitter: a good place to detect health conditions | Prieto, Matos, Alvarez, Cacheda, Oliveira | 2014 | Depression, Eating Disorders | |
| Detecting Suicidal Ideation in Chinese Microblogs with Psychological Lexicons | Huang, Zhang, Liu, Chiu, Li, Zhu | Sina Weibo | 2014 | Suicidal Ideation |
| Toward Macro-Insights for Suicide Prevention: Analyzing Fine-Grained Distress at Scale | Homan, Johar, Liu, Lytle, Silenzio, Alm | 2014 | Distress Level | |
| Affective and content analysis of online depression communities | Nguyen, Phung, Dao, Venkatesh, Berk | LiveJournal | 2014 | Depression, Self-Harm, Suicide, Bipolar Disorder, Grief |
| Defining patients with depressive disorder by using textual information | Nakamura, Kubo, Usuda, Aramaki | TOBYO Toshoshitsu (Disease Survivor Blogs) | 2014 | Depression |
| A depression detection model based on sentiment analysis in micro-blog social network | Wang, Zhang, Ji, Sun, Wu, Bao | Sina Weibo | 2013 | Depression |
| Activities on Facebook Reveal the Depressive State of Users | Park, Lee, Kwak, Cha, Jeong | 2013 | Depression | |
| An improved model for depression detecting in micro-blog social network | Wang, Zhang, Sun | Sina Weibo | 2013 | Depression |
| Perception Differences between the Depressed and Non-Depressed Users in Twitter | Park, McDonald, Cha | 2013 | Depression | |
| Predicting Depression via Social Media | De Choudhury, Gamon, Counts, Horvitz | 2013 | Depression | |
| Social Media As a Measurement Tool of Depression in Populations | De Choudhury, Counts, Horvitz | 2013 | Depression | |
| Suicide Ideation of Individuals in Online Social Networks | Masuda, Kurahashi, Onari | Mixi | 2013 | Suicidal Ideation |
| Exploiting Temporal Information in a Two-Stage Classification Framework for Content-Based Depression | Shen, Kuo, Chen, Lin | PTT (Bulletin Board System) | 2013 | Depression |
| On estimating depressive tendency of twitter users from their tweet data | Tsugawa, Mogi, Kikuchi, Kishino, Fujita, Itoh, Ohsaki | 2013 | Depression | |
| Predicting postpartum changes in emotion and behavior via social media | De Choudhury, Counts, Horvitz | 2013 | Behavioral Change for New Mothers (re: Postpartum Depression | |
| Depressive Moods of Users Portrayed in Twitter | Park, Cha, Cha | 2012 | Depression, Control |