Search Results for author: Glen Coppersmith

Found 18 papers, 2 papers with code

Individual Differences in the Movement-Mood Relationship in Digital Life Data

no code implementations NAACL (CLPsych) 2021 Glen Coppersmith, Alex Fine, Patrick Crutchley, Joshua Carroll

We describe these individual differences, and argue that individual variability in the relationship between movement and mood is one of many such factors that ought be taken into account in wellbeing-focused apps and AI systems.

Social media data as a lens onto care-seeking behavior among women veterans of the US armed forces

no code implementations EMNLP (NLP+CSS) 2020 Kacie Kelly, Alex Fine, Glen Coppersmith

In this article, we examine social media data as a lens onto support-seeking among women veterans of the US armed forces.

Assessing population-level symptoms of anxiety, depression, and suicide risk in real time using NLP applied to social media data

no code implementations EMNLP (NLP+CSS) 2020 Alex Fine, Patrick Crutchley, Jenny Blase, Joshua Carroll, Glen Coppersmith

Here, we demonstrate that natural language processing applied to publicly-available social media data can provide real-time estimates of psychological distress in the population (specifically, English-speaking Twitter users in the US).

Decision Making

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

no code implementations NAACL (CLPsych) 2021 Sean MacAvaney, Anjali Mittu, Glen Coppersmith, Jeff Leintz, Philip Resnik

Progress on NLP for mental health — indeed, for healthcare in general — is hampered by obstacles to shared, community-level access to relevant data.

Predictive Linguistic Features of Schizophrenia

no code implementations SEMEVAL 2017 Efsun Sarioglu Kayi, Mona Diab, Luca Pauselli, Michael Compton, Glen Coppersmith

As such, we examine the writings of schizophrenia patients analyzing their syntax, semantics and pragmatics.

In your wildest dreams: the language and psychological features of dreams

no code implementations WS 2017 Kate Niederhoffer, Jonathan Schler, Patrick Crutchley, Kate Loveys, Glen Coppersmith

In this paper, we provide the first quantified exploration of the structure of the language of dreams, their linguistic style and emotional content.

Decision Making General Classification +2

Quantifying Mental Health from Social Media with Neural User Embeddings

1 code implementation30 Apr 2017 Silvio Amir, Glen Coppersmith, Paula Carvalho, Mário J. Silva, Byron C. Wallace

Our experimental results demonstrate that the user embeddings capture similarities between users with respect to mental conditions, and are predictive of mental health.

Representation Learning

Ethical Research Protocols for Social Media Health Research

no code implementations WS 2017 Adrian Benton, Glen Coppersmith, Mark Dredze

Social media have transformed data-driven research in political science, the social sciences, health, and medicine.

Decision Making Ethics

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