ArticleJMIR mental health2020
Analyzing Trends of Loneliness Through Large-Scale Analysis of Social Media Postings: Observational Study.
Article in JMIR mental health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Digital social contacts predict reduced loneliness in chronic depression: an exploratory longitudinal study.European archives of psychiatry and clinical neuroscience · 2026Observational
- Understanding Health-Related Discussions on Reddit: Development of a Topic Assignment Method and Exploratory Analysis.JMIR formative research · 2025Article
- Exploring Reddit conversations about mental health difficulties among college students during the COVID-19 pandemic.Journal of American college health : J of ACH · 2024Article
- Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learning.Scientific reports · 2024Article
- Harnessing Artificial Intelligence for Health Message Generation: The Folic Acid Message Engine.Journal of medical Internet research · 2022Article
- Young Sexual Minority Adolescent Experiences of Self-expression and Isolation on Social Media: Cross-sectional Survey Study.JMIR mental health · 2021Article
- The Relationship Between Loneliness and Psychological Adjustment: Validation of the Italian Version of the Interpersonal Acceptance-Rejection Loneliness Scale.Frontiers in psychology · 2021Article
- Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study.JMIR infodemiologyArticle
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Authors and funding
2 authors.
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Abstract
backgroundLoneliness has become a public health problem described as an epidemic, and it has been argued that digital behavior such as social media posting affects loneliness.
objectiveThe aim of this study is to expand knowledge of the determinants of loneliness by investigating online postings in a social media forum devoted to loneliness. Specifically, this study aims to analyze the temporal trends in loneliness and their associations with topics of interest, especially with those related to mental health determinants.
methodsWe collected a total of 19,668 postings from 11,054 users in the loneliness forum on Reddit. We asked seven crowdsourced workers to imagine themselves as writing 1 of 236 randomly chosen posts and to answer the short-form UCLA Loneliness Scale. After showing that these postings could provide an assessment of loneliness, we built a predictive model for loneliness scores based on the posts' text and applied it to all collected postings. We then analyzed trends in loneliness postings over time and their correlations with other topics of interest related to mental health determinants.
resultsWe found that crowdsourced workers can estimate loneliness (interclass correlation=0.19) and that predictive models are correlated with reported loneliness scores (Pearson r=0.38). Our results show that increases in loneliness are strongly associated with postings to a suicidality-related forum (hazard ratio 1.19) and to forums associated with other detrimental behaviors such as depression and illicit drug use. Clustering demonstrates that people who are lonely come from diverse demographics and from a variety of interests.
conclusionsThe results demonstrate that it is possible for unrelated individuals to assess people's social media postings for loneliness. Moreover, our findings show the multidimensional nature of online loneliness and its correlated behaviors. Our study shows the advantages of studying a hard-to-reach population through social media and suggests new directions for future studies.
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