Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Jul;57(7):994-1003.
doi: 10.1177/00048674221126649. Epub 2022 Oct 14.

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  1   2 , Ulrich S Tran  2   3 , Hubert Baginski  4   5 , Mark Sinyor  6   7 , Markus J Strauss  1 , Steven A Sumner  8 , Martin Voracek  2   3 , Benedikt Till  1   2 , Sean Murphy  9 , Frances Gonzalez  9 , Madelyn Gould  10 , David Garcia  4   11 , John Draper  9 , Hannah Metzler  1   4   11
Affiliations

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 et al. Aust N Z J Psychiatry. 2023 Jul.

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 × 10-5, standard error = 2.6 × 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.

Keywords: Papageno effect; Twitter; United States; help-seeking; interrupted time series; media effects; social media; suicide; suicide prevention.

PubMed Disclaimer

Conflict of interest statement

Declaration of Conflicting Interests

The author(s) disclosed receipt of the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: T.N. and B.T. were partially funded by a grant from Vibrant Emotional Health related to this project. S.M., F.G. and J.D. are employees of Vibrant Emotional Health and provided data on calls to the Lifeline, as well as contributed to revising this report and approved its submission. There was no other involvement of the funding source.

Figures

Figure 1.
Figure 1.
Number of tweets, tweets for each content category, Suicide Prevention Lifeline calls and suicides from 1 January 2016 to 31 December 2018, United States. The light blue trend line was made with ggplot2 in R (version 3.3.5) via generalized additive model (GAM) smoothing with default parameters (Wickham, 2016).
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Bray P (2012) When Is My Tweet’s Prime of Life? (A Brief Statistical Interlude) Available at: https://moz.com/blog/when-is-my-tweets-prime-of-life (accessed 16 May 2022).
    1. Burnap P, Colombo G, Amery R, et al. (2017) Multi-class machine classification of suicide-related communication on Twitter. Online Social Networks and Media 2: 32–44. - PMC - PubMed
    1. Devlin J, Chang MW, Lee K, et al. (2019) BERT: Pre-training of deep bidirectional transformers for language understanding Available at: http://arxiv.org/abs/1810.04805 (accessed 26 July 2021).
    1. Fahey RA, Matsubayashi T and Ueda M (2018). Tracking the Werther Effect on social media: Emotional responses to prominent suicide deaths on Twitter and subsequent increases in suicide. Social Science & Medicine 219: 19–29. - PubMed
    1. International Association for Suicide Prevention (2020) World suicide prevention day 2020: Impact report Available at: www.iasp.info/wspd2020/ (accessed 26 July 2021).