Digital footprints as means of measuring loneliness experience and embeddedness in social networks for designing digital mental health interventions

Abstract

Introduction & Background Despite existing research evidence for the negative influence of loneliness on people’s wellbeing, most studies focus on the experiences of older adults and the student population. Moreover, research concerning loneliness and digital footprints uses demographic proxies, as opposed to a behavioural focus, thus providing an incomplete representation of the phenomenon’s influence on the general population. Objectives & Approach This project aims to use people’s digital social media data (shared by the participants from their Facebook, Twitter, or Reddit accounts) to address people’s experiences of loneliness in order to provide guidance for the design of interventions catering to the improvement of the wellbeing of individuals. Screening the participants for loneliness levels using the UCLA Loneliness Scale and looking how these experiences differ cross-sectionally (25-65-year-olds; minorities) will help understand the following: social network structures, as shaped by loneliness experience; the dynamics within one’s social network; and the linguistic content of the relationships. Using digital footprints for language modelling and thematic analysis of digital language data shared by the participants, in addition to social network analysis (mapped out based on the individuals’ digital interactions) will allow insight into digital wellbeing. A traditional approach will be utilised alongside digital data analysis to address the issue of limited social media data representativeness - relationships formed in non-digital settings, along with the associated loneliness experiences, will be included. In addition to sharing their digital footprints, the participants will be surveyed and interviewed about their everyday offline and digital experiences of loneliness; as well as their social network structures and dynamics. The interview and survey data will be analysed using thematic analysis of text data and predictive models of quantitative survey responses; in addition to social network analysis of the relationships listed during the interview. Predictions of loneliness outcomes in relation to people’s digital and offline behaviour; and correlations between loneliness experiences and social network dynamics will be made from the data. Relevance to Digital Footprints The project focuses on people’s experiences of loneliness in both digital and offline settings utilising the analysis of digital footprints from social media and traditional survey- and interview-based methodology. This approach will allow to gain insight into the similarities and differences between social network structures and dynamics as well as loneliness experiences in digital and real-world relationships as these inevitably interplay in everyday life. The inclusion of digital footprints data will allow to measure and predict loneliness impact on mental health and digital social behaviour; and design tailored digital wellbeing interventions in the future. Conclusions & Implications The results will serve as basis for designing innovative loneliness interventions for both the public and counsellors to offer tailored wellbeing support. Additionally, the project aims to promote loneliness awareness. Incorporating a variety of experiences from different social groups will enable inclusive, user-centred approach.

Keywords

• social networks
• social network analysis
• loneliness
• digital footprints
• wellbeing