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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Revealing the relationship between rational fatalism and the online privacy paradox.

an article by Wenjing Xie (Marist College, Poughkeepsie, NY, USA) and Amy Fowler-Dawson and Anita Tvauri (Southern Illinois University Carbondale, IL, USA) published in Behaviour & Information Technology Volume 38 Issue 7 (2019)

Abstract

Previous research has revealed the privacy paradox, which suggests that despite concern about their online privacy, people still reveal a large amount of personal information and don’t take measures to protect personal privacy online.

Using data from a national-wide survey, this study takes a psychological approach and uses the rational fatalism theory to explain the privacy paradox on the Internet and the social networking sites (SNSs). The rational fatalism theory argues that risks will become rational if the person believes he or she has no control over the outcome.

Our results support the rational fatalism view. We found that people with higher levels of fatalistic belief about technologies and business are less likely to protect their privacy on the Internet in general, and the SNS in particular.

Moreover, such relationship is stronger among young Internet users compared with older users.

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The influence of personality traits and social networks on the self-disclosure behavior of social network site users

an article by Xi Chen, Yin Pan and Bin Guo (Zhejiang University, Hangzhou, China) published in Internet Research Volume 26 Issue 3 (2016)

Abstract

Purpose
The purpose of this paper is to determine the influence and interaction of social networks and personality traits on the self-disclosure behavior of social network site (SNS) users. According to social capital theory and the Big Five personality model, the authors hypothesized that social capital factors would affect the accuracy and amount of self-disclosure behavior and that personality traits would moderate this effect.

Design/methodology/approach
A survey was conducted to collect data from 207 SNS users. The questionnaire was administered in university classrooms and libraries and via e-mail. The measurement model and structural model were examined by using LISREL 8.8 and SmartPLS 2.0.

Findings
Based on the path analysis, the authors identified several interesting patterns to explain self-disclosure behavior on SNSs. First, the centrality of SNS users has a positive effect on their amount of self-disclosure. Moreover, people who are more extroverted disclose personal information that is more accurate with the level of the cognitive dimension held constant and disclose a greater amount of personal information with the level of the structural dimension held constant. From a practical perspective, the results may provide useful insight for companies operating SNSs.

Originality/value
This study analyzed the influence of social capital factors on SNS users’ self-disclosure, as well as the interactions between personality and social capital factors. Specifically, the authors examined six important variables of social capital divided into three dimensions. This research complements current research on SNSs by focusing on SNS users’ motivation to disclose self-related information in addition to information sharing.

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