Alone together online: a mixed-methods analysis of loneliness, recognition, and peer response in a public digital community
Résumé
Introduction: Loneliness is a significant public health concern, yet most research relies on survey-based methods that capture prevalence and correlates rather than the experiential and social texture of how loneliness is described and responded to in everyday settings. This study examined loneliness-related discourse in r/lonely, one of the largest public subreddits dedicated to the topic. Methods: The study used a convergent mixed-methods design combining large-scale computational text analysis and Braun and Clarke reflexive thematic analysis. The computational strand analyzed 877,799 comments using sentiment analysis, emotion analysis, topic modeling, and keyword co-occurrence network analysis. The qualitative strand analyzed a purposive high-engagement sample of 80 posts and 478 associated comments for thread-based analysis in ATLAS.ti. Results: Five themes were developed: plural forms of loneliness; longing and accumulated disappointment; gendered loneliness and contested recognition; uneven peer support; and rejection of misrecognizing advice. Computational findings showed that positive sentiment and supportive emotional language were prominent at scale, but the qualitative analysis revealed substantial variation in response quality, including predatory behavior, gendered dismissal, and forms of misrecognition that compounded rather than addressed loneliness. Discussion: The findings contribute to understanding loneliness as a multidimensional, socially negotiated condition shaped by relational injury and the uneven politics of recognition in public digital communities.
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