Emma Samsioe
Biträdande universitetslektor
#50+ fashion Instagram influencers : cognitive age and aesthetic digital labours
Författare
Summary, in English
Purpose: This paper demonstrates how #50+ fashion Instagram influencers contribute to the social construction of cognitive age through their aesthetic digital labours. Design/methodology/approach: Non-participative netnography was used in the form of visual and textual analysis of over 300 Instagram posts including images, captions and comments. Findings: Findings reveal how outfit selection, background choices and bodily poses redefine expressions of look age through forms of aesthetic labour. Post-construction, hashtag and emoji usage illustrates how influencers refrain from directly posting about the fashion brands that they endorse. Instead, image and personality work visually attracts followers to politically charged posts which directly impact upon the social and cultural contexts where influencers are active. This ties into present-day wider societal discourses. Practical implications: 50+ fashion influencers have high spending power. Fashion brands should refrain from using #brand and collaborate in more subtle ways and concentrate on challenging the negativity of the old-age cliché. Originality/value: The study advances theory on the social construction of age in fashion studies by combining cognitive age with aesthetic labour to identify the characteristics of the social phenomenon of the 50+ Instagram influencer. It applies principles from critical visual analysis to digital context, thereby advancing the qualitative netnographic toolkit.
Avdelning/ar
- Institutionen för tjänstevetenskap
Publiceringsår
2020-04-10
Språk
Engelska
Sidor
399-413
Publikation/Tidskrift/Serie
Journal of Fashion Marketing and Management
Volym
24
Issue
3
Dokumenttyp
Artikel i tidskrift
Förlag
Emerald Group Publishing Limited
Ämne
- Sociology (excluding Social Work, Social Psychology and Social Anthropology)
- Cultural Studies
Nyckelord
- Aesthetic labour
- Age
- Fashion
- Influencer
- Netnography
- Visual analysis
Status
Published
ISBN/ISSN/Övrigt
- ISSN: 1361-2026