ArticleBMC public health2022
Text mining for identifying the nature of online questions about non-suicidal self-injury.
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Computational text analysis of emotional expressions related to non-suicidal self-injury in Chinese social media.Scientific reports · 2026Article
- When "Self-Harm" Means "Suicide": A Topic Modeling Study of Adolescent Online Help-Seeking for Self-Harm.Suicide & life-threatening behavior · 2025Article
- Non-suicidal self-injury motivation scale in a community sample of adolescents: a methodological study.BMC psychology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe internet provides convenient access to information about non-suicidal self-injury (NSSI) owing to its accessibility and anonymity. This study aimed to explore the distribution of topics regarding NSSI posted on the internet and yearly trends in the derived topics using text mining.
methodsWe searched for the keyword "non-suicidal self-injury" (Ja-Hae in Korean) in the Naver Q&A using the statistical package R. We analyzed 7893 NSSI-related questions posted between 2009 and 2018. Text mining was performed using latent Dirichlet allocation (LDA) on the dataset to determine associations between phrases and thus identify common themes in posts about NSSI.
resultsIn the LDA, we selected the following 10 most common topics: anger, family troubles, collecting information on NSSI, stress, concerns regarding NSSI scarring, ways to help a non-suicidal self-injurious friend, depression, medical advice, ways to perform or stop NSSI, and prejudices and thoughts regarding non-suicidal self-injurious people.
conclusionsThis study provides valuable information on the nature of NSSI questions posted online. In future research, developing websites that provide NSSI information and support or guidance on effectively communicating with NSSI is necessary.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.