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. 2021 Dec 29;19(1):343.
doi: 10.3390/ijerph19010343.

A Pilot Case-Control Study of the Social Media Activity Following Cluster and Non-Cluster Suicides in Australia

Phillip Cheuk Fung Law  1 , Lay San Too  1 , Nicole T M Hill  2   3 , Jo Robinson  4   5 , Madelyn Gould  6 , Jo-An Occhipinti  7   8 , Matthew J Spittal  1 , Katrina Witt  4   5 , Mark Sinyor  9 , Benedikt Till  10 , Nathaniel Osgood  11 , Ante Prodan  7   12 , Rifat Zahan  11 , Jane Pirkis  1
Affiliations

A Pilot Case-Control Study of the Social Media Activity Following Cluster and Non-Cluster Suicides in Australia

Phillip Cheuk Fung Law et al. Int J Environ Res Public Health. .

Abstract

Social media may play a role in the "contagion" mechanism thought to underpin suicide clusters. Our pilot case-control study presented a novel methodological approach to examining whether Facebook activity following cluster and non-cluster suicides differed. We used a scan statistic to identify suicide cluster cases occurring in spatiotemporal clusters and matched each case to 10 non-cluster control suicides. We identified the Facebook accounts of 3/48 cluster cases and 20/480 non-cluster controls and their respective friends-lists and retrieved 48 posthumous posts and replies (text segments) referring to the deceased for the former and 606 for the latter. We examined text segments for "putatively harmful" and "putatively protective" content (e.g., discussion of the suicide method vs. messages discouraging suicidal acts). We also used concept mapping, word-emotion association, and sentiment analysis and gauged user reactions to posts using the reactions-to-posts ratio. We found no "putatively harmful" or "putatively protective" content following any suicides. However, "family" and "son" concepts were more common for cluster cases and "xx", "sorry" and "loss" concepts were more common for non-cluster controls, and there were twice as many surprise- and disgust-associated words for cluster cases. Posts pertaining to non-cluster controls were four times as receptive as those about cluster cases. We hope that the approach we have presented may help to guide future research to explain suicide clusters and social-media contagion.

Keywords: clusters; contagion; social media; suicide.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Leximancer concept map for (a) the cluster cases and (b) the non-cluster controls.
Figure 2
Figure 2
List of the 10 most frequent words associated with each NRC lexicon emotion in (a) the cluster cases and (b) the non-cluster controls. * Indicates the most frequent words for an emotion for this group that do not fall among the most frequent words for the same emotion in the other group. Words that are not marked with * are common in both groups. The frequency of words is denoted along the x-axis.
Figure 3
Figure 3
List of the 10 most frequent words associated with NRC lexicon sentiments in (a) the cluster cases and (b) the non-cluster controls. * the most frequent words for a sentiment for this group that do not fall among the most frequent words for the same sentiment in the other group. Words that are not marked with * are common in both groups. The frequency of words is denoted along the x-axis.
See this image and copyright information in PMC

References

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