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


Yates,  Andrew
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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MacAvaney, S., Desmet, B., Cohan, A., Soldaini, L., Yates, A., Zirikly, A., et al. (2018). RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses. Retrieved from http://arxiv.org/abs/1806.07916.

Cite as: https://hdl.handle.net/21.11116/0000-0002-5ED9-1
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.