Minority Ethnic Vulnerabilities in the Use of Digital Housing Services Across Age Groups

Despite the accelerated digitalisation of social housing services, there has been a lack of focused attention to the harms that are likely to arise through the systemic inequalities encountered by minoritised ethnic (ME) communities in the UK. Within this context, we are employing an intersectional framework to underline the centrality of age to ME vulnerabilities including lack of digital literacy and proficiency in English in the access, use and outcomes of digitalised social housing services. We draw our findings from an interdisciplinary sentimental analysis of 100 interviews with ME individuals in Glasgow, Bradford, Manchester and Tower Hamlets for extracting vulnerabilities and assessing their intensities across different ME age groups, and a subsample of qualitative analysis of 21 interviews. This is to illustrate similarities and differences of sentimental analysis of these vulnerabilities between machine learning (ML) and inductive coding, offering an example for future ML supported qualitative data analysis approach in housing studies.