Dataset Open Access

Reddit Mental Health Dataset

Low, Daniel M.; Rumker, Laurie; Talker, Tanya; Torous, John; Cecchi, Guillermo; Ghosh, Satrajit S.


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    <dct:title>Reddit Mental Health Dataset</dct:title>
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    <dcat:keyword>Natural Language Processing</dcat:keyword>
    <dcat:keyword>Mental Health</dcat:keyword>
    <dcat:keyword>Psychiatry</dcat:keyword>
    <dcat:keyword>COVID-19</dcat:keyword>
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    <dct:description>&lt;div&gt;&amp;nbsp;&lt;/div&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; &lt;p&gt;This dataset contains posts from 28 subreddits (15 mental health support groups) from 2018-2020. We used this dataset to understand the impact of COVID-19 on mental health support groups from January to April, 2020&amp;nbsp;and included older timeframes to obtain baseline&amp;nbsp;posts before COVID-19.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Please cite if you use this dataset:&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Low, D. M., Rumker, L., Torous, J., Cecchi, G., Ghosh, S. S., &amp;amp; Talkar, T. (2020). Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study.&amp;nbsp;&lt;em&gt;Journal of medical Internet research&lt;/em&gt;,&amp;nbsp;&lt;em&gt;22&lt;/em&gt;(10), e22635.&lt;/p&gt; &lt;pre&gt;@article{low2020natural, title={Natural Language Processing Reveals Vulnerable Mental Health Support Groups and Heightened Health Anxiety on Reddit During COVID-19: Observational Study}, author={Low, Daniel M and Rumker, Laurie and Torous, John and Cecchi, Guillermo and Ghosh, Satrajit S and Talkar, Tanya}, journal={Journal of medical Internet research}, volume={22}, number={10}, pages={e22635}, year={2020}, publisher={JMIR Publications Inc., Toronto, Canada} }&lt;/pre&gt; &lt;p&gt;&lt;br&gt; &lt;strong&gt;License&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;This dataset is made available under the Public Domain Dedication and License v1.0 whose full text can be found at:&amp;nbsp;&lt;a href="http://www.opendatacommons.org/licenses/pddl/1.0/"&gt;http://www.opendatacommons.org/licenses/pddl/1.0/&lt;/a&gt;&lt;/p&gt; &lt;p&gt;It was downloaded using pushshift API. Re-use of this data is subject to Reddit API terms.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Reddit Mental Health Dataset&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Contains posts and text features for the following timeframes from 28 mental health and non-mental health subreddits:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;&lt;strong&gt;15 specific mental health support groups&lt;/strong&gt;&amp;nbsp;(r/EDAnonymous, r/addiction, r/alcoholism, r/adhd, r/anxiety, r/autism, r/bipolarreddit, r/bpd, r/depression, r/healthanxiety, r/lonely, r/ptsd, r/schizophrenia, r/socialanxiety, and r/suicidewatch)&lt;/li&gt; &lt;li&gt;&lt;strong&gt;2 broad mental health&lt;/strong&gt;&amp;nbsp;subreddits (r/mentalhealth, r/COVID19_support)&lt;/li&gt; &lt;li&gt;&lt;strong&gt;11 non-mental health subreddits&lt;/strong&gt;&amp;nbsp;(r/conspiracy, r/divorce, r/fitness, r/guns, r/jokes, r/legaladvice, r/meditation, r/parenting, r/personalfinance, r/relationships, r/teaching).&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;code&gt;filenames&lt;/code&gt;&amp;nbsp;and corresponding timeframes:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;&lt;code&gt;post:&lt;/code&gt;&amp;nbsp;Jan 1 to April 20, 2020 (called &amp;quot;mid-pandemic&amp;quot; in manuscript; r/COVID19_support appears).&amp;nbsp;Unique users: 320,364.&amp;nbsp;&lt;/li&gt; &lt;li&gt;&lt;code&gt;pre:&lt;/code&gt;&amp;nbsp;Dec 2018 to Dec 2019. A full year which provides more data for a baseline of Reddit posts.&amp;nbsp;Unique users: 327,289.&lt;/li&gt; &lt;li&gt;&lt;code&gt;2019:&lt;/code&gt;&amp;nbsp;Jan 1 to April 20, 2019 (r/EDAnonymous appears). A control for seasonal fluctuations to match&amp;nbsp;&lt;code&gt;post&lt;/code&gt;&amp;nbsp;data.&amp;nbsp;Unique users: 282,560.&lt;/li&gt; &lt;li&gt;&lt;code&gt;2018:&lt;/code&gt;&amp;nbsp;Jan 1 to April 20, 2018. A control for seasonal fluctuations to match&amp;nbsp;&lt;code&gt;post&lt;/code&gt;&amp;nbsp;data.&amp;nbsp;Unique users: 177,089&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;Unique users across all time windows (pre and 2019 overlap): 826,961.&lt;/p&gt; &lt;p&gt;See manuscript Supplementary Materials (https://doi.org/10.31234/osf.io/xvwcy) for more information.&lt;/p&gt; &lt;p&gt;Note: if subsampling (e.g., to balance subreddits), we recommend bootstrapping analyses for unbiased results.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;</dct:description>
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