Digital communication plays a crucial role in social interactions, social network maintenance and people’s mental wellbeing (Masur, 2021; Meier et al., 2016). With language data providing insights into social network dynamics (Liu et al., 2022), gossip is an important component of social interactions (Yucel et al., 2021) and lack thereof.

Loneliness, inevitably associated with social interactions, has increased in recent years due to the COVID-19 pandemic and the associated social changes (Kovacs et al., 2021). The perspectives of marginalised groups such as LGBTQ+, disabled and neurodivergent people are often misunderstood and dismissed with regard to loneliness and social dynamics (Mellifont, 2021; Armitage & Nellums, 2020; Garcia et al., 2019). In addition, past research has identified issues with studies investigating loneliness as a phenomenon, such as the under-representation of adults aged 25-65, with most data coming from young (18-21) and older adults (65+); as well as the need to consider behavioural data in future research (Reedman-Flint et al., 2022).

Considering the above problems, this PhD project aims to cross-sectionally understand people’s sense of embeddedness in their digital and offline social networks. Drawing on the experiences of adults aged 18-65 years old (allowing for the inclusion of 18-24 year-olds due to the numerous social transitions typically happening around that age); the LGBTQ+ community as well as disabled and neurodivergent people outside of clinical settings, the analysis will allow us to gain insight into the dynamics of social networks, language patterns as well as the role of gossip in interactions within social groups.

The inclusion of marginalised voices in this research project will allow to design tailored interventions for improved wellbeing, including both digital self-help resources as well as guidance for counsellors.

The proposed methodology will be of mixed nature. Participants will be invited to take part in interviews and complete surveys on their social network dynamics and loneliness experiences. Minority group membership will be considered amongst the demographic information collected as well as lived experiences, where appropriate. Additionally, the participants will be asked to share their digital footprint data for language and social network insights. 

The data will be analysed using a mixed-methods approach: combining quantitative and qualitative language analysis methods, in addition to social network analysis and predictive models.

This PhD project will contribute to the understanding of the social network dynamics and loneliness experiences of disabled, neurodivergent and LGTBQ+ people; in addition to expanding on the existing knowledge of the above for the general adult population. This approach will allow to design and implement digital wellbeing interventions tailored to the user’s needs.

The project is running in partnership with B:friend – a befriending charity offering support to lonely older adults. The work is supported by the Engineering and Physical Research Council [Grant number EP/S023305/1].