The Role of Embeddedness in Social Networks in People’s Digital and Offline Experiences of Loneliness

This project examines how loneliness affects socialization and assesses the role of gossip on human communication in offline and online settings.

  • Funder


  • Duration

    Sept 2023 – Sept 2027

  • Investigators

    Bogna Liziniewicz, Dr. John Harvey, Prof. James Goulding, and Dr. Liz Dowthwaite.

Project Description

This project focuses on the structures and dynamics of people’s social networks in both digital and offline settings. Under consideration are the influence of loneliness experiences on socialisation processes, as well as the role of gossip as a measurement of communication in human interaction. Among the goals of the project is i) to investigate how the social network of an individual changes over time, as measured through language insights and social network analysis and ii) to gain an understanding of the functioning of social relationships within interpersonal networks.

Including a variety of social groups (i.e., adults aged 18-65; older adults; LGBTQ+ people, disabled people, neurodivergent people), this project aims to find out how different or similar the experiences of loneliness and people’s social networks can be. The results of this project can contribute to the development of tailored, real-life loneliness interventions which will help improve health and wellbeing.


The proposed methodology will include measurement of loneliness levels among the participants; collection of social network data as well as demographic information; a series of interviews to gain an in-depth understanding of the participants’ social relationships and loneliness experiences; in addition to social media data donation. 

The proposed data analysis methods will focus on social network analysis; language analysis using social media data and interviews; and predictive models for loneliness outcomes. The aim is to gain an understanding of the relationship between loneliness levels and the individuals’ social network functioning, as well as to predict loneliness outcomes based on people’s demographics and experiences, in order to contribute to the design of tailored, innovative, digital wellbeing interventions.



Associated Publications

Media, Blogs and News Stories