Peer-reviewed Research

We believe that the state-of-the-art improves most quickly when research is shared with the greater community. Our ground-breaking research regularly appears in peer-reviewed scientific publications.

We are also pioneers in the ethical application of this field of technology, with the first published ethical framework and recommendations for doing health research with social media data.

2021

Individual differences in the Movement-Mood Relationship in Digital Life Data.

Glen Coppersmith, Alex Fine, Patrick Crutchley, Joshua Carroll.

Community-level research on Suicidality Prediction in a Secure Environment: Overview of the CLPsych 2021 Shared Task.

Sean Macavaney, Anjali Mittu, Glen Coppersmith, Jeff Leintz, Philip Resnik.

Can language use in social media help in the treatment of severe mental illness?

Deanna Kelly, Max Spaderna, Vedrana Hodzic, Glen Coppersmith, Shuo Chen, Philip Resnik.

Bibliometric Studies and the Discipline of Social Media Mental Health Research.

Philip Resnik, Munmun De Choudhury, Katherine Musacchio Shafer, Glen Coppersmith.

2020

Assessing Population-level Symptoms of Anxiety, Depression, and Suicide Risk in Real Time using NLP applied to Social Media Data.

Alex Fine, Patrick Crutchley, Jenny Blase, Joshua Carroll, Glen Coppersmith.

Social Media Data as a lens onto Care-seeking Behavior among Women Veterans of the US Armed Forces.

Kacie Kelly, Alex Fine, Glen Coppersmith.

Blinded Clinical Ratings of Social Media Data are Correlated with In-Person Clinical Ratings in Participants Diagnosed with Either Depression, Schizophrenia, or Healthy Controls.

Deanna Kelly, Max Spaderna, Vedrana Hodzic, Suraj Nair, Christopher Kitchen, Anne Werkheiser, Megan Powell, Fang Liu, Glen Coppersmith, Shuo Chen, Philip Resnik.

Early warning signs of a mental health tsunami: A coordinated response to gather initial data insights from multiple digital services providers.

Becky Inkster et al. (including Glen Coppersmith and Alex Fine.)

Implementation Determinants and Outcomes of a Technology-Enabled Service Targeting Suicide Risk in High Schools: Mixed Methods Study.

Molly Adrian, Jessica Coifman, Michael Pullmann, Jennifer Blossom, Casey Chandler, Glen Coppersmith, Paul Thompson, Aaron Lyon.

2018

Natural Language Processing of Social Media as Screening for Suicide Risk.

Glen Coppersmith, Ryan Leary, Patrick Crutchley, Alex Fine.

Cross-Cultural Differences in Language Markers of Depression Online.

Kate Loveys, Jonathan Torrez, Alex Fine, Glen Moriarty, Glen Coppersmith.

Distil: A Mixed-Initiative Model Discovery System for Subject Matter Experts.

Scott Langevin, David Jonker, Christopher Bethune, Glen Coppersmith, Casey Hilland, Jonathon Morgan, Paul Azunre, Justin Gawrilow.

2017

Scalable Mental Health Analysis in the Clinical Whitespace via Natural Language Processing.

Glen Coppersmith, Casey Hilland, Ophir Frieder, Ryan Leary.

Understanding Depressive Symptoms and Psychosocial Stressors on Twitter: A Corpus-Based Study.

Danielle Mowery, Hillary Smith, Tyler Cheney, Greg Stoddard, Glen Coppersmith, Craig Bryan, Mike Conway.

Clinical Validation of Models Built from Self-Stated Diagnosis Social Media Data.

Glen Coppersmith, Patrick Crutchley, Raina M Merchant, H. Andrew Schwartz.

Small but Mighty: Affective Micropatterns for Quantifying Mental Health from Social Media Language.

Kate Loveys, Patrick Crutchley, Emily Wyatt, Glen Coppersmith.

Ethical Research Protocols for Social Media Health Research.

Adrian Benton, Glen Coppersmith, Mark Dredze.

Unobtrusive Analysis of Mental Health on Social Media via User Embeddings.

Silvio Amir, Byron Wallace, Glen Coppersmith, Paula Carvalho, Mario Silva.

In Your Wildest Dreams: the language of psychological features of dreams.

Kate Neiderhoffer, Jonathan Schler, Patrick Crutchley, Kate Loveys, Glen Coppersmith.

2016

Exploratory Analysis of Social Media Prior to a Suicide Attempt.

Glen Coppersmith, Kim Ngo, Ryan Leary, Tony Wood.

Quantifying Suicidal Ideation on Twitter.

Tony Wood, Jesse Shiffman, Ryan Leary, Glen Coppersmith.

The Clinical Panel: Leveraging Psychological Expertise During NLP Research.

Glen Coppersmith, Kristy Hollingshead, H. Andrew Schwartz, Molly Ireland, Rebecca Resnik, Kate Loveys, April Foreman, Loring Ingraham.

Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media.

Munmun De Choudhury, Emre Kiciman, Mark Dredze, Glen Coppersmith, Mrinal Kumar.

Demographer: Extremely Simple Name Demographics.

Rebecca Knowles, Josh Carroll, Mark Dredze.

2015

Quantifying Suicidal Ideation via Language Usage on Social Media.

Glen Coppersmith, Tony Wood, Ryan Leary, Eric Whyne.

From ADHD to SAD: analyzing the language of mental health on Twitter through self-reported diagnoses.

Glen Coppersmith, Mark Dredze, Craig Harman, Kristy Hollingshead.

Introduction to the CLPsych-2015 Shared and Unshared Tasks: Depression vs. PTSD on Twitter.

Glen Coppersmith, Mark Dredze, Craig Harman, Kristy Hollingshead, Margaret Mitchell.

Quantifying the language of Schizophrenia in Social Media.

Margaret Mitchell, Kristy Hollingshead, Glen Coppersmith.

Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides.

Mrinal Kumar, Mark Dredze, Glen Coppersmith, Munmun De Choudhury.

2014

Quantifying Mental Health Signals in Twitter.

Glen Coppersmith, Mark Dredze, Craig Harman.

Measuring Post Traumatic Stress Disorder in Twitter.

Glen Coppersmith, Craig Harman, Mark Dredze.