Introducing a more-than-quantitative approach to explore emerging structures of feeling in the everyday

•With an estimated 5 billion people worldwide owning a smart device of some kind and variously engaged with social media platforms and generating social media data, our living world is more device/application centric and datafied than ever before, generating an emerging, evolving contemporary struct...

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Veröffentlicht in:Emotion, space and society space and society, 2023-11, Vol.49, p.100965, Article 100965
Hauptverfasser: Bennett, Katy, De Sabbata, Stefano
Format: Artikel
Sprache:eng
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Zusammenfassung:•With an estimated 5 billion people worldwide owning a smart device of some kind and variously engaged with social media platforms and generating social media data, our living world is more device/application centric and datafied than ever before, generating an emerging, evolving contemporary structure of feeling. We argue in this intervention that we need to advance quantitative approaches and techniques, alongside interdisciplinary working, to engage with this emerging structure of feeling and to reimagine emotion, space and society.•This intervention is agenda shaping in terms of introducing a more than quantitative approach that involves an interdisciplinary research team working together with algorithms and blackbox artificial intelligence models to quantify what we struggle to qualify in terms of the everyday and how it is experienced. Our approach introduces are quantitative (and qualitative) methods alongside our practices of working together involving listening, empathy and trust.•This intervention takes a creative approach, at times involving a conversation between two Geographers (one with a background in Computer Science and quantitative approaches, the other in ethnographic and qualitative approaches) as they explore the limitations and opportunities of theoretical and computational capabilities and interdisciplinary working.•The intervention shows interdisciplinary, quantitative work in progress, putting into practice what others have suggested and written about in terms of potential, advantages, disadvantages, opportunities and challenges of social media data analysis.
ISSN:1755-4586
1878-0040
DOI:10.1016/j.emospa.2023.100965