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JMIR Ment Health. 2019 Dec 6;6(12):e13076. doi: 10.2196/13076.

Identifying Sleep-Deprived Authors of Tweets: Prospective Study.

Author information

1
University of California Institute for Prediction Technology, Los Angeles, CA, United States.
2
Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
3
New York University-Winthrop Hospital, Mineola, NY, United States.
4
Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, United States.
5
Department of Medicine, University of California, Irvine, Orange, CA, United States.
6
University of California Institute for Prediction Technology, Irvine, CA, United States.

Abstract

BACKGROUND:

Social media data can be explored as a tool to detect sleep deprivation. First-year undergraduate students in their first quarter were invited to wear sleep-tracking devices (Basis; Intel), allow us to follow them on Twitter, and complete weekly surveys regarding their sleep.

OBJECTIVE:

This study aimed to determine whether social media data can be used to monitor sleep deprivation.

METHODS:

The sleep data obtained from the device were utilized to create a tiredness model that aided in labeling the tweets as sleep deprived or not at the time of posting. Labeled data were used to train and test a gated recurrent unit (GRU) neural network as to whether or not study participants were sleep deprived at the time of posting.

RESULTS:

Results from the GRU neural network suggest that it is possible to classify the sleep-deprivation status of a tweet's author with an average area under the curve of 0.68.

CONCLUSIONS:

It is feasible to use social media to identify students' sleep deprivation. The results add to the body of research suggesting that social media data should be further explored as a potential source for monitoring health.

KEYWORDS:

information storage and retrieval; natural language processing; neural networks (computer); safety; sleep; sleep deprivation; social media; wearable electronic devices

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