Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning
Background: Suicide and substance use disorder (SUD) pose serious public health challenges among young adults in the United States. Increasing social media use among these populations can be leveraged as an alternative method to detect characteristics of suicide-related topics and behavior among sub...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-05-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2021.551296/full |
| _version_ | 1819095292236005376 |
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| author | Vidya Purushothaman Vidya Purushothaman Jiawei Li Tim K. Mackey Tim K. Mackey Tim K. Mackey Tim K. Mackey |
| author_facet | Vidya Purushothaman Vidya Purushothaman Jiawei Li Tim K. Mackey Tim K. Mackey Tim K. Mackey Tim K. Mackey |
| author_sort | Vidya Purushothaman |
| collection | DOAJ |
| description | Background: Suicide and substance use disorder (SUD) pose serious public health challenges among young adults in the United States. Increasing social media use among these populations can be leveraged as an alternative method to detect characteristics of suicide-related topics and behavior among substance users.Objective: To detect and characterize suicide and self-harm related conversations co-occurring with SUD posts and comments on the popular social media platform Instagram.Methods: This study used big data and machine learning approaches to collect and classify Instagram posts containing 632 controlled substance-related hashtags. Posts were first classified for online drug diversion topics and then filtered to detect suicide and mental health discussions. Posts and comments were then manually annotated for SUD and mental health co-occurring themes. Associations between these characteristics were tested using the Chi-square test.Results: We detected 719 Instagram posts/comments that included user-generated discussions about suicide, substance use and/or mental health. Posts self-reporting SUD and mental health topics were also more likely to discuss suicide compared to those that did not discuss SUD and mental health topics, respectively (p < 0.001). Major themes observed included concurrent discussions of suicide ideation and attempts and low self-esteem.Conclusions: Our study results provide preliminary evidence of social media discussions about suicide and mental health among those with SUD. This co-occurrence represents a key health risk factor on a platform heavily utilized by young adults. Further studies are required to analyze specific patterns of suicide and self-harm ideations for the purposes of designing future suicide prevention campaigns through digital channels. |
| first_indexed | 2024-12-21T23:40:59Z |
| format | Article |
| id | doaj.art-c0b002756e2d4e07b3cfd5ca5b8fde39 |
| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-12-21T23:40:59Z |
| publishDate | 2021-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj.art-c0b002756e2d4e07b3cfd5ca5b8fde392022-12-21T18:46:14ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402021-05-011210.3389/fpsyt.2021.551296551296Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine LearningVidya Purushothaman0Vidya Purushothaman1Jiawei Li2Tim K. Mackey3Tim K. Mackey4Tim K. Mackey5Tim K. Mackey6Masters in Public Health Program, University of California, San Diego, San Diego, CA, United StatesDepartment of Anesthesiology, School of Medicine, University of California, San Diego, San Diego, CA, United StatesDepartment of Healthcare Research and Policy, University of California San Diego - Extension, San Diego, CA, United StatesDepartment of Anesthesiology, School of Medicine, University of California, San Diego, San Diego, CA, United StatesDepartment of Healthcare Research and Policy, University of California San Diego - Extension, San Diego, CA, United StatesGlobal Health Policy and Data Institute, San Diego, CA, United StatesDivision of Infectious Disease and Global Public Health, Department of Medicine, School of Medicine, University of California, San Diego, San Diego, CA, United StatesBackground: Suicide and substance use disorder (SUD) pose serious public health challenges among young adults in the United States. Increasing social media use among these populations can be leveraged as an alternative method to detect characteristics of suicide-related topics and behavior among substance users.Objective: To detect and characterize suicide and self-harm related conversations co-occurring with SUD posts and comments on the popular social media platform Instagram.Methods: This study used big data and machine learning approaches to collect and classify Instagram posts containing 632 controlled substance-related hashtags. Posts were first classified for online drug diversion topics and then filtered to detect suicide and mental health discussions. Posts and comments were then manually annotated for SUD and mental health co-occurring themes. Associations between these characteristics were tested using the Chi-square test.Results: We detected 719 Instagram posts/comments that included user-generated discussions about suicide, substance use and/or mental health. Posts self-reporting SUD and mental health topics were also more likely to discuss suicide compared to those that did not discuss SUD and mental health topics, respectively (p < 0.001). Major themes observed included concurrent discussions of suicide ideation and attempts and low self-esteem.Conclusions: Our study results provide preliminary evidence of social media discussions about suicide and mental health among those with SUD. This co-occurrence represents a key health risk factor on a platform heavily utilized by young adults. Further studies are required to analyze specific patterns of suicide and self-harm ideations for the purposes of designing future suicide prevention campaigns through digital channels.https://www.frontiersin.org/articles/10.3389/fpsyt.2021.551296/fullsuicidesubstance abusesocial mediaInstagramopioidsmachine learning |
| spellingShingle | Vidya Purushothaman Vidya Purushothaman Jiawei Li Tim K. Mackey Tim K. Mackey Tim K. Mackey Tim K. Mackey Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning Frontiers in Psychiatry suicide substance abuse social media opioids machine learning |
| title | Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning |
| title_full | Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning |
| title_fullStr | Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning |
| title_full_unstemmed | Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning |
| title_short | Detecting Suicide and Self-Harm Discussions Among Opioid Substance Users on Instagram Using Machine Learning |
| title_sort | detecting suicide and self harm discussions among opioid substance users on instagram using machine learning |
| topic | suicide substance abuse social media opioids machine learning |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2021.551296/full |
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