Search Results for author: Keith Harrigian

Found 10 papers, 5 papers with code

Towards Understanding the Role of Gender in Deploying Social Media-Based Mental Health Surveillance Models

no code implementations NAACL (CLPsych) 2021 Eli Sherman, Keith Harrigian, Carlos Aguirre, Mark Dredze

Spurred by advances in machine learning and natural language processing, developing social media-based mental health surveillance models has received substantial recent attention.

Then and Now: Quantifying the Longitudinal Validity of Self-Disclosed Depression Diagnoses

no code implementations NAACL (CLPsych) 2022 Keith Harrigian, Mark Dredze

Self-disclosed mental health diagnoses, which serve as ground truth annotations of mental health status in the absence of clinical measures, underpin the conclusions behind most computational studies of mental health language from the last decade.

Selection bias

The Problem of Semantic Shift in Longitudinal Monitoring of Social Media: A Case Study on Mental Health During the COVID-19 Pandemic

1 code implementation22 Jun 2022 Keith Harrigian, Mark Dredze

Social media allows researchers to track societal and cultural changes over time based on language analysis tools.

Gender and Racial Fairness in Depression Research using Social Media

no code implementations EACL 2021 Carlos Aguirre, Keith Harrigian, Mark Dredze

While previous research has raised concerns about possible biases in models produced from this data, no study has quantified how these biases actually manifest themselves with respect to different demographic groups, such as gender and racial/ethnic groups.

Fairness

On the State of Social Media Data for Mental Health Research

1 code implementation NAACL (CLPsych) 2021 Keith Harrigian, Carlos Aguirre, Mark Dredze

Data-driven methods for mental health treatment and surveillance have become a major focus in computational science research in the last decade.

Do Models of Mental Health Based on Social Media Data Generalize?

1 code implementation Findings of the Association for Computational Linguistics 2020 Keith Harrigian, Carlos Aguirre, Mark Dredze

Proxy-based methods for annotating mental health status in social media have grown popular in computational research due to their ability to gather large training samples.

Geocoding Without Geotags: A Text-based Approach for reddit

1 code implementation WS 2018 Keith Harrigian

In this paper, we introduce the first geolocation inference approach for reddit, a social media platform where user pseudonymity has thus far made supervised demographic inference difficult to implement and validate.

Recognizing Film Entities in Podcasts

no code implementations24 Sep 2018 Ahmet Salih Gundogdu, Arjun Sanghvi, Keith Harrigian

In this paper, we propose a Named Entity Recognition (NER) system to identify film titles in podcast audio.

named-entity-recognition Named Entity Recognition +1

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