Ethno-racial identity and digitalisation in self-presentation: a large-scale Instagram content analysis

This study addresses the question to which extent individual online self-presentations become more similar globally, due globalisation and digitalisation, or whether ethno-racial identity predisposes individuals’ online self-presentation. That is, we examined the degree to which individuals varying in ethno-racial identity converge or diverge in online self-presentation. A large-scale content analysis was conducted by collecting selfies on Instagram (i.e. #selfietime; N = 3881). Using facial recognition software, selfies were allotted into a specific ethno-racial identity based on race/ethnicity-related appearance features (e.g. Asian, Black, Hispanic, and White identity) as a proxy for externally imposed ethno-racial identity. Results provided some evidence for convergence in online self-construction among selfie-takers, but generally revealed that self-presentations diverge as a function of ethno-racial identity. That is, results showed more convergence between ethno-racial identity for portraying selfies with objectified elements, whereas divergence in online self-presentations occurred for portraying contextualised selves and filter usage. In all, this study examined the complexity of online self-presentation. Here, we extend earlier cross-cultural research by exploring the convergence-divergence paradigm for the role of externally imposed ethno-racial identity in online self-presentation. Findings imply that ethno-racial identity characteristics remain important in manifestations of online self-presentations.