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Attentional Social Media: Mapping the Spaces and Networks of the Fashion Industry

Author

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  • Ate Poorthuis
  • Dominic Power
  • Matthew Zook

Abstract

In this article we use big data methods to analyze the attention paid to the fashion industry on social media. The article argues that for the fashion industry, like many industries, the core product is a form of knowledge that is dependent on gaining and holding people’s attention. To understand this attentional economy, social media offers a unique window because it is increasingly a central space within which fashion knowledge is created and shared. Using long-term, geotagged big data from Twitter, we analyze the hitherto difficult-to-explore spaces and places of the global fashion industry. The article suggests that the data confirm the ideas that there are a series of global fashion capitals that are especially important to the industry and that attention paid to fashion is highly uneven and varied across industry functions, national origins, and companies. Evidence is presented that attention to fashion is a global phenomenon that does not always directly link to where fashion products are sold. Attention to fashion is both a market-making mechanism for the industry as well as an indicator of wider social and cultural processes of tastemaking and identity formation within which fashion is entwined. The article concludes by suggesting that such data offer geographers new ways of looking at and linking economic, social, and cultural spaces and geographies and that social media analysis can help bridge boundaries that divide geographers. Key Words: attention economy, big data, economic geography, fashion industry, social media.

Suggested Citation

  • Ate Poorthuis & Dominic Power & Matthew Zook, 2020. "Attentional Social Media: Mapping the Spaces and Networks of the Fashion Industry," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 110(4), pages 941-966, July.
  • Handle: RePEc:taf:raagxx:v:110:y:2020:i:4:p:941-966
    DOI: 10.1080/24694452.2019.1664887
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    Cited by:

    1. Karen Chapple & Ate Poorthuis & Matthew Zook & Eva Phillips, 2022. "Monitoring streets through tweets: Using user-generated geographic information to predict gentrification and displacement," Environment and Planning B, , vol. 49(2), pages 704-721, February.

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