暂无分享,去创建一个
Mark Dredze | Keith Harrigian | Carlos Aguirre | Mark Dredze | Carlos Alejandro Aguirre | Keith Harrigian
[1] Rada Mihalcea,et al. Text-Based Detection and Understanding of Changes in Mental Health , 2018, SocInfo.
[2] Mark Dredze,et al. Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides , 2015, HT.
[3] Suchi Saria,et al. Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist , 2020, Nature Medicine.
[4] Marti A. Hearst,et al. Towards augmenting crisis counselor training by improving message retrieval , 2019, Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology.
[5] Bethany A. Teachman,et al. Identification of Imminent Suicide Risk Among Young Adults using Text Messages , 2018, CHI.
[6] Munmun De Choudhury,et al. A Social Media Based Index of Mental Well-Being in College Campuses , 2017, CHI.
[7] Munmun De Choudhury,et al. Gender and Cross-Cultural Differences in Social Media Disclosures of Mental Illness , 2017, CSCW.
[8] Gautam Srivastava,et al. A Decentralized Privacy-Preserving Healthcare Blockchain for IoT , 2019, Sensors.
[9] Munmun De Choudhury,et al. Modeling Stress with Social Media Around Incidents of Gun Violence on College Campuses , 2017, Proc. ACM Hum. Comput. Interact..
[10] S. Bucci,et al. The digital revolution and its impact on mental health care. , 2019, Psychology and psychotherapy.
[11] Lei Zhang,et al. Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users , 2014, HCC.
[12] Munmun De Choudhury,et al. Anorexia on Tumblr: A Characterization Study , 2015, Digital Health.
[13] Minsu Park,et al. Depressive Moods of Users Portrayed in Twitter , 2012 .
[14] Bart Desmet,et al. SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions , 2018, COLING.
[15] Tat-Seng Chua,et al. What Does Social Media Say about Your Stress? , 2016, IJCAI.
[16] Mark Dredze,et al. Mental Health Surveillance over Social Media with Digital Cohorts , 2019, Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology.
[17] Yoav Goldberg,et al. Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them , 2019, NAACL-HLT.
[18] Miguel A. Vadillo,et al. Researching Mental Health Disorders in the Era of Social Media: Systematic Review , 2017, Journal of medical Internet research.
[19] James Pustejovsky,et al. Distinguishing Clinical Sentiment: The Importance of Domain Adaptation in Psychiatric Patient Health Records , 2019, Proceedings of the 2nd Clinical Natural Language Processing Workshop.
[20] Galen Panger. Reassessing the Facebook experiment: critical thinking about the validity of Big Data research , 2016 .
[21] Fabio Crestani,et al. eRISK 2017: CLEF Lab on Early Risk Prediction on the Internet: Experimental Foundations , 2017, CLEF.
[22] W. Price,et al. Privacy in the age of medical big data , 2019, Nature Medicine.
[23] Sharath Chandra Guntuku,et al. Detecting depression and mental illness on social media: an integrative review , 2017, Current Opinion in Behavioral Sciences.
[24] Munmun De Choudhury,et al. Recovery Amid Pro-Anorexia: Analysis of Recovery in Social Media , 2016, CHI.
[25] Chirag Shah,et al. What social media data should i use in my research?: A comparative analysis of twitter, youtube, reddit, and the new york times comments , 2016, ASIST.
[26] D. Asch,et al. Facebook language predicts depression in medical records , 2018, Proceedings of the National Academy of Sciences.
[27] Philip Resnik,et al. Expert, Crowdsourced, and Machine Assessment of Suicide Risk via Online Postings , 2018, CLPsych@NAACL-HTL.
[28] David DeVault,et al. The Distress Analysis Interview Corpus of human and computer interviews , 2014, LREC.
[29] Munmun De Choudhury,et al. Measuring the Impact of Anxiety on Online Social Interactions , 2018, ICWSM.
[30] Mark Dredze,et al. Do Models of Mental Health Based on Social Media Data Generalize? , 2020, FINDINGS.
[31] Munmun De Choudhury,et al. The Language of Social Support in Social Media and Its Effect on Suicidal Ideation Risk , 2017, ICWSM.
[32] Madhu C. Reddy,et al. Sharing Patient-Generated Data in Clinical Practices: An Interview Study , 2016, AMIA.
[33] Stefan Scherer,et al. What type of happiness are you looking for? - A closer look at detecting mental health from language , 2018, CLPsych@NAACL-HTL.
[34] Solon Barocas,et al. Language (Technology) is Power: A Critical Survey of “Bias” in NLP , 2020, ACL.
[35] Mark Dredze,et al. Shared Task : Depression and PTSD on Twitter , 2015 .
[36] Nazli Goharian,et al. Depression and Self-Harm Risk Assessment in Online Forums , 2017, EMNLP.
[37] Maarten Sap,et al. Towards Assessing Changes in Degree of Depression through Facebook , 2014, CLPsych@ACL.
[38] J. Ayers,et al. Seasonality in seeking mental health information on Google. , 2013, American journal of preventive medicine.
[39] Mark Dredze,et al. Quantifying Mental Health Signals in Twitter , 2014, CLPsych@ACL.
[40] Micah Iserman,et al. Within and Between-Person Differences in Language Used Across Anxiety Support and Neutral Reddit Communities , 2018, CLPsych@NAACL-HTL.
[41] Daniel Jurafsky,et al. Automatic Detection of Incoherent Speech for Diagnosing Schizophrenia , 2018, CLPsych@NAACL-HTL.
[42] Mark Dredze,et al. Ethical Research Protocols for Social Media Health Research , 2017, EthNLP@EACL.
[43] Munmun De Choudhury,et al. Norms Matter: Contrasting Social Support Around Behavior Change in Online Weight Loss Communities , 2018, CHI.
[44] Mike Conway,et al. Towards Automatically Classifying Depressive Symptoms from Twitter Data for Population Health , 2016, PEOPLES@COLING.
[45] Glen Coppersmith,et al. Exploratory Analysis of Social Media Prior to a Suicide Attempt , 2016, CLPsych@HLT-NAACL.
[46] David C. Atkins,et al. Smartphone-Based Passive Assessment of Mobility in Depression: Challenges and Opportunities. , 2018, Mental health and physical activity.
[47] C. Fuchs. Culture and Economy in the Age of Social Media , 2015 .
[48] Michael D. Barnes,et al. Tracking suicide risk factors through Twitter in the US. , 2014, Crisis.
[49] Mike Conway,et al. Towards Developing an Annotation Scheme for Depressive Disorder Symptoms: A Preliminary Study using Twitter Data , 2015, CLPsych@HLT-NAACL.
[50] Kathleen M. Carley,et al. A Hierarchical Location Prediction Neural Network for Twitter User Geolocation , 2019, EMNLP.
[51] Alexander Benlian,et al. User Dynamics in Mental Health Forums - A Sentiment Analysis Perspective , 2019, Wirtschaftsinformatik.
[52] Rafael A. Calvo,et al. CLPsych 2016 Shared Task: Triaging content in online peer-support forums , 2016, CLPsych@HLT-NAACL.
[53] Frank Rudzicz,et al. Detecting Anxiety through Reddit , 2017, CLPsych@ACL.
[54] C. Faravelli,et al. Assessment of depression: a comparison of rating scales. , 1986, Journal of affective disorders.
[55] P. Resnik,et al. CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts , 2019, Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology.
[56] Munmun De Choudhury,et al. Methodological Gaps in Predicting Mental Health States from Social Media: Triangulating Diagnostic Signals , 2019, CHI.
[57] Mark Dredze,et al. From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses , 2015, CLPsych@HLT-NAACL.
[58] John Marcotte,et al. ICPSR Virtual Data Enclave as a Collaboratory for Team Science , 2019 .
[59] Tat-Seng Chua,et al. Depression Detection via Harvesting Social Media: A Multimodal Dictionary Learning Solution , 2017, IJCAI.
[60] Ahmed M. Elmisery,et al. Privacy Preserving Distributed Learning Clustering of HealthCare Data Using Cryptography Protocols , 2010, COMPSAC Workshops.
[61] Jan Snajder,et al. Not Just Depressed: Bipolar Disorder Prediction on Reddit , 2018, WASSA@EMNLP.
[62] Eric Horvitz,et al. Predicting Depression via Social Media , 2013, ICWSM.
[63] Glen Coppersmith,et al. Cross-cultural differences in language markers of depression online , 2018, CLPsych@NAACL-HTL.
[64] M. Millard,et al. Detecting Linguistic Traces of Depression in Topic-Restricted Text: Attending to Self-Stigmatized Depression with NLP , 2018 .
[65] Fabio Crestani,et al. Overview of eRisk: Early Risk Prediction on the Internet (Extended Lab Overview) , 2018, CLEF.
[66] Kathleen McKeown,et al. Dreaddit: A Reddit Dataset for Stress Analysis in Social Media , 2019, EMNLP.
[67] Sejin Park,et al. The role of social media in local government crisis communications , 2015 .
[68] M. Gorelick,et al. Bias arising from missing data in predictive models. , 2006, Journal of clinical epidemiology.
[69] Maria Liakata,et al. The language of mental health problems in social media , 2016, CLPsych@HLT-NAACL.
[70] Douglas M. Blough,et al. Data obfuscation: anonymity and desensitization of usable data sets , 2004, IEEE Security & Privacy Magazine.
[71] Çağrı Çöltekin,et al. Identifying Depression on Reddit: The Effect of Training Data , 2018, EMNLP 2018.
[72] Bart Desmet,et al. RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses , 2018, CLPsych@NAACL-HTL.
[73] G. Arbanas. Diagnostic and Statistical Manual of Mental Disorders (DSM-5) , 2015 .
[74] A. Anderson. Social Media Use in 2018 , 2018 .
[75] Mark Dredze,et al. Measuring Post Traumatic Stress Disorder in Twitter , 2014, ICWSM.
[76] Munmun De Choudhury,et al. Quantifying and Predicting Mental Illness Severity in Online Pro-Eating Disorder Communities , 2016, CSCW.
[77] Stevie Chancellor,et al. Methods in predictive techniques for mental health status on social media: a critical review , 2020, npj Digital Medicine.
[78] Mark Dredze,et al. Using Noisy Self-Reports to Predict Twitter User Demographics , 2020, SOCIALNLP.
[79] Mark Dredze,et al. Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media , 2016, CHI.