Abstract
Increasing numbers of individuals describe themselves as feeling lonely, regardless of age, gender or geographic location. This article investigates how social media users self-disclose feelings of loneliness, and how they seek and provide support to each other. Motivated by related studies in this area, a dataset of 22,477 Twitter posts sent over a one-week period was analyzed using both qualitative and quantitative methods. Through a thematic analysis, we demonstrate that self-disclosure of perceived loneliness takes a variety of forms, from simple statements of “I'm lonely”, through to detailed self-reflections of the underlying causes of loneliness. The analysis also reveals forms of online support provided to those who are feeling lonely. Further, we conducted a quantitative linguistic content analysis of the dataset which revealed patterns in the data, including that ‘lonely’ tweets were significantly more negative than those in a control sample, with levels of negativity fluctuating throughout the week and posts sent at night being more negative than those sent in the daytime.
Original language | English |
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Pages (from-to) | 20-30 |
Number of pages | 11 |
Journal | Computers in Human Behavior |
Volume | 98 |
Early online date | 24 Mar 2019 |
DOIs | |
Publication status | Published - 30 Sept 2019 |
Keywords
- Loneliness
- Self-disclosure
- Social media
ASJC Scopus subject areas
- Arts and Humanities (miscellaneous)
- Human-Computer Interaction
- General Psychology