Evidence map›Paper›PMID 35340901›Full record

ArticleDigital health

Understanding information behavior of South Korean Twitter users who express suicidality on Twitter.

Donghun Kim, Woojin Jung, Seojin Nam, Hongjin Jeon, Jihyun Baek, Yongjun Zhu

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Donghun KimDepartment of Library and Information Science, Sungkyunkwan University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-5441-1532
Woojin JungDepartment of Library and Information Science, Sungkyunkwan University, Seoul, Republic of Korea.
Seojin NamDepartment of Library and Information Science, Sungkyunkwan University, Seoul, Republic of Korea.
Hongjin JeonDepartment of Psychiatry, School of Medicine, Sungkyunkwan University, Seoul, Republic of Korea.
Jihyun BaekDepartment of Psychiatry, School of Medicine, Sungkyunkwan University, Seoul, Republic of Korea.
Yongjun ZhuDepartment of Library and Information Science, Yonsei University, Seoul, Republic of Korea.
Sungkyunkwan University · KRSamsung Medical Center · KRYonsei University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Although there were few studies on how suicidal users behave on Twitter, they only investigated partial aspects such as tweeting frequency and tweet length. Therefore, we aim to understand the various information behavior of suicidal users in South Korea. Methods: To achieve this goal, we annotated 20,000 tweets and identified 1097 tweets with the expression of suicidality (i.e. suicidal tweets) and 229 suicidal users (i.e. experimental group). Using the data, a user profile analysis, comparative analysis with control group, and tweets/hashtags analysis were performed. Results: Our results show that many suicidal users used suicide-related keywords in their user IDs, usernames, descriptions, and pinned tweets. We also found that, compared to the control group, the experimental group show different patterns of information behavior. The experimental group did not frequently use Twitter and, on average, wrote longer texts than the control group. A clear seasonal pattern was also identified in the experimental group's tweeting behavior. Frequently used keywords/hashtags were extracted from tweets written by the experimental group for the purpose of understanding their concerns and detecting more suicidal tweets. Conclusions: We believe that our study will help in the understanding of suicidal users' information behavior on social media and lay the basis for more accurate actions for suicide prevention and early intervention on social media.

Indexed as

Data analysisdiseasehealth communicationinformaticsmediapublic healthpublic health informaticssocial media

Identifiers

PMID35340901
PMCPMC8943454
OpenAlexW4221021557

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.