RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses

TL;DR

This paper introduces RSDD-Time, a dataset of Reddit posts with detailed temporal annotations of self-reported depression diagnoses, enabling better analysis of mental health over time in social media.

Contribution

The creation of RSDD-Time dataset with comprehensive temporal annotations for self-reported mental health diagnoses on social media.

Findings

Temporal information extraction is challenging.

Baseline models show room for improvement.

Dataset facilitates longitudinal mental health studies.

Abstract

Self-reported diagnosis statements have been widely employed in studying language related to mental health in social media. However, existing research has largely ignored the temporality of mental health diagnoses. In this work, we introduce RSDD-Time: a new dataset of 598 manually annotated self-reported depression diagnosis posts from Reddit that include temporal information about the diagnosis. Annotations include whether a mental health condition is present and how recently the diagnosis happened. Furthermore, we include exact temporal spans that relate to the date of diagnosis. This information is valuable for various computational methods to examine mental health through social media because one's mental health state is not static. We also test several baseline classification and extraction approaches, which suggest that extracting temporal information from self-reported diagnosis statements is challenging.