Feeling alone among 317 million others: Disclosures of loneliness on Twitter

an article by Jamie Mahoney, Effie Le Moignan, John Vines and Shaun Lawson (Northumbria University, Newcastle-upon-Tyne, UK) Kiel Long (Lancaster University, Bailrigg, UK), Mike Wilson (Loughborough University, UK) and Julie Barnett (University of Bath, Claverton Down, UK) published in Computers in Human Behavior Volume 98 (September 2019)

Highlights

• Twitter is used to both seek and provide support regarding loneliness.
• Language in these disclosures differ when related to the day and time of disclosure.
• Weekend and night-time disclosures are associated with the angriest language.
• A range of disclosures suggest that user behaviour may develop over time.

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.

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