Celebrity suicide on Twitter : Activity, content and network analysis related to the death of Swedish DJ Tim Bergling alias Avicii

dc.contributor.authorNiederkrotenthaler, Thomas
dc.contributor.authorTill, Benedikt
dc.contributor.authorGarcia, David
dc.date.accessioned2023-01-19T09:21:27Z
dc.date.available2023-01-19T09:21:27Z
dc.date.issued2019eng
dc.description.abstractBackground
Media recommendations for suicide reporting are recommended to prevent imitative suicide but little is known about social media reactions to different revelations about celebrity suicide.

Methods
Using the Twitter Application Programming Interface (API), we recorded public tweets mentioning Avicii from the day when his death was reported (N = 2,865,292). We compared that data with a dataset of random tweets. Furthermore, we recorded tweets including suicide in 124 languages before Avicii‘s death (N = 5,939,107). We processed English tweets mentioning Avicii with the Linguistic Inquiry and Word Count (LIWC) to quantify the frequency of affects and related linguistic signals. We also processed the text of tweets to detect tweets mentioning the suicide method, and we retrieved the list of followers of users who tweeted about the method. We constructed reply networks from the dataset, analysing three networks corresponding to the major news events about Avicii‘s death.

Results
Avicii's suicide sparked immediate strong interest with both positive (χ² = 781.06, p < 10−6) and negative emotional expressions (χ² = 1518.5, p < 10−6) in comparison to baseline levels. Subsequent revelations were associated with smaller peaks with mainly negative emotional content after Avicii's death was revealed as a suicide (χ² = 33.2, p < 10−6 and after news about the suicide method (χ² = 274.93, p < 10−6). Tweeting about the suicide method was infrequent, but twitter users who covered the method had more followers that users who did not (D = 0.1675, p < 10−6; t = 19.87, p < 10−6), and a noteworthy number of users had considerable exposure to the suicide method.

Limitations
This was a descriptive analysis.

Conclusions
Twitter users showed strong interest in news about Avicii's death and Avicii's suicide, but less so in the suicide method, and showed distinct tweeting behaviours based on the different revelations.
eng
dc.description.versionpublishedeng
dc.identifier.doi10.1016/j.jad.2018.11.071eng
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/59813
dc.language.isoengeng
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dc.rights.urihttps://rightsstatements.org/page/InC/1.0/
dc.subject.ddc320eng
dc.titleCelebrity suicide on Twitter : Activity, content and network analysis related to the death of Swedish DJ Tim Bergling alias Aviciieng
dc.typeJOURNAL_ARTICLEeng
dspace.entity.typePublication
kops.citation.bibtex
@article{Niederkrotenthaler2019Celeb-59813,
  year={2019},
  doi={10.1016/j.jad.2018.11.071},
  title={Celebrity suicide on Twitter : Activity, content and network analysis related to the death of Swedish DJ Tim Bergling alias Avicii},
  volume={245},
  issn={0165-0327},
  journal={Journal of Affective Disorders},
  pages={848--855},
  author={Niederkrotenthaler, Thomas and Till, Benedikt and Garcia, David}
}
kops.citation.iso690NIEDERKROTENTHALER, Thomas, Benedikt TILL, David GARCIA, 2019. Celebrity suicide on Twitter : Activity, content and network analysis related to the death of Swedish DJ Tim Bergling alias Avicii. In: Journal of Affective Disorders. Elsevier. 2019, 245, pp. 848-855. ISSN 0165-0327. eISSN 1573-2517. Available under: doi: 10.1016/j.jad.2018.11.071deu
kops.citation.iso690NIEDERKROTENTHALER, Thomas, Benedikt TILL, David GARCIA, 2019. Celebrity suicide on Twitter : Activity, content and network analysis related to the death of Swedish DJ Tim Bergling alias Avicii. In: Journal of Affective Disorders. Elsevier. 2019, 245, pp. 848-855. ISSN 0165-0327. eISSN 1573-2517. Available under: doi: 10.1016/j.jad.2018.11.071eng
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    <dcterms:abstract xml:lang="eng">Background&lt;br /&gt;Media recommendations for suicide reporting are recommended to prevent imitative suicide but little is known about social media reactions to different revelations about celebrity suicide.&lt;br /&gt;&lt;br /&gt;Methods&lt;br /&gt;Using the Twitter Application Programming Interface (API), we recorded public tweets mentioning Avicii from the day when his death was reported (N = 2,865,292). We compared that data with a dataset of random tweets. Furthermore, we recorded tweets including suicide in 124 languages before Avicii‘s death (N = 5,939,107). We processed English tweets mentioning Avicii with the Linguistic Inquiry and Word Count (LIWC) to quantify the frequency of affects and related linguistic signals. We also processed the text of tweets to detect tweets mentioning the suicide method, and we retrieved the list of followers of users who tweeted about the method. We constructed reply networks from the dataset, analysing three networks corresponding to the major news events about Avicii‘s death.&lt;br /&gt;&lt;br /&gt;Results&lt;br /&gt;Avicii's suicide sparked immediate strong interest with both positive (χ² = 781.06, p &lt; 10&lt;sup&gt;−6&lt;/sup&gt;) and negative emotional expressions (χ² = 1518.5, p &lt; 10&lt;sup&gt;−6&lt;/sup&gt;) in comparison to baseline levels. Subsequent revelations were associated with smaller peaks with mainly negative emotional content after Avicii's death was revealed as a suicide (χ² = 33.2, p &lt; 10&lt;sup&gt;−6&lt;/sup&gt; and after news about the suicide method (χ² = 274.93, p &lt; 10&lt;sup&gt;−6&lt;/sup&gt;). Tweeting about the suicide method was infrequent, but twitter users who covered the method had more followers that users who did not (D = 0.1675, p &lt; 10&lt;sup&gt;−6&lt;/sup&gt;; t = 19.87, p &lt; 10&lt;sup&gt;−6&lt;/sup&gt;), and a noteworthy number of users had considerable exposure to the suicide method.&lt;br /&gt;&lt;br /&gt;Limitations&lt;br /&gt;This was a descriptive analysis.&lt;br /&gt;&lt;br /&gt;Conclusions&lt;br /&gt;Twitter users showed strong interest in news about Avicii's death and Avicii's suicide, but less so in the suicide method, and showed distinct tweeting behaviours based on the different revelations.</dcterms:abstract>
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