Skip to main navigation Skip to search Skip to main content

Association of 7 million+ tweets featuring suicide-related content with daily calls to the Suicide Prevention Lifeline and with suicides, United States, 2016-2018

  • Thomas Niederkrotenthaler
  • , Ulrich Tran
  • , H. Baginski
  • , Mark Sinyor
  • , M.J. Strauss
  • , S.A. Sumner
  • , Martin Voracek
  • , Benedikt Till
  • , S. Murphy
  • , F. Gonzalez
  • , M. Gould
  • , D. Garcia
  • , J. Draper
  • , Hannah Metzler

Publications: Contribution to journal › Article › Peer Reviewed

Abstract

Objective: The aim of this study was to assess associations of various content areas of Twitter posts with help-seeking from the US National Suicide Prevention Lifeline (Lifeline) and with suicides. Methods: We retrieved 7,150,610 suicide-related tweets geolocated to the United States and posted between 1 January 2016 and 31 December 2018. Using a specially devised machine-learning approach, we categorized posts into content about prevention, suicide awareness, personal suicidal ideation without coping, personal coping and recovery, suicide cases and other. We then applied seasonal autoregressive integrated moving average analyses to assess associations of tweet categories with daily calls to the US National Suicide Prevention Lifeline (Lifeline) and suicides on the same day. We hypothesized that coping-related and prevention-related tweets are associated with greater help-seeking and potentially fewer suicides. Results: The percentage of posts per category was 15.4% (standard deviation: 7.6%) for awareness, 13.8% (standard deviation: 9.4%) for prevention, 12.3% (standard deviation: 9.1%) for suicide cases, 2.4% (standard deviation: 2.1%) for suicidal ideation without coping and 0.8% (standard deviation: 1.7%) for coping posts. Tweets about prevention were positively associated with Lifeline calls (B = 1.94, SE = 0.73, p = 0.008) and negatively associated with suicides (B = -0.11, standard error = 0.05, p = 0.038). Total number of tweets were negatively associated with calls (B = -0.01, standard error = 0.0003, p = 0.007) and positively associated with suicide, (B = 6.4 x 10(-5), standard error = 2.6 x 10(-5), p = 0.015). Conclusion: This is the first large-scale study to suggest that daily volume of specific suicide-prevention-related social media content on Twitter corresponds to higher daily levels of help-seeking behaviour and lower daily number of suicide deaths. Preregistration: As Predicted, #66922, 26 May 2021.

Original languageEnglish
Pages (from-to)994-1003
Number of pages10
JournalAustralian & New Zealand Journal of Psychiatry
Volume57
Issue number7
Early online date14 Oct 2022
DOIs
Publication statusPublished - Jul 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Austrian Fields of Science 2012

  • 501022 Suicidology

Keywords

  • Twitter
  • suicide
  • help-seeking
  • suicide prevention
  • interrupted time series
  • Papageno effect
  • social media
  • media effects
  • United States
  • SUBSEQUENT INCREASES
  • PROMINENT SUICIDE
  • MEDIA REPORTS
  • TWITTER
  • DEATHS
  • TRACKING
  • RISK

Fingerprint

Dive into the research topics of 'Association of 7 million+ tweets featuring suicide-related content with daily calls to the Suicide Prevention Lifeline and with suicides, United States, 2016-2018'. Together they form a unique fingerprint.

Cite this