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Use of Image Recognition of Social Media
Umeå University. (Digital Media Lab)ORCID iD: 0000-0002-9283-9246
Edith Cowan University.
Umeå University.
Umeå University. (Digital Media Lab)
2017 (English)In: ANZMAC 2017: Marketing for Impact: Conference Proceedings / [ed] Linda Robinson, Linda Brennan, Mike Reid, Melbourne: RMIT University , 2017, p. 271-278Conference paper, Published paper (Refereed)
Abstract [en]

Images are central to firms in their use of social media platforms as part of their marketing strategy. Images are a powerful online marketing tool as they allow for engagement and personalisation of marketing content for individual customers. However, images can be a double edge sword in the web 2.0 world, where consumers are able to post content to branded social media sites. This study evaluates the benefits of integrating image recognition into social media from the users perspective. The pilot study undertaken found the majority of the participants thought the possibilities presented for image recognition technology are useful, however they showed concern in relation to their privacy if this technology were to be in social media networks. The results also showed that prior familiarity with this technology does not have any significant impact in how social media users feel about having this technology in social media.

Place, publisher, year, edition, pages
Melbourne: RMIT University , 2017. p. 271-278
Series
Proceedings, ISSN 1447-3275
Keywords [en]
Image recognition, social media, privacy
National Category
Interaction Technologies Media Engineering Signal Processing
Identifiers
URN: urn:nbn:se:umu:diva-144319OAI: oai:DiVA.org:umu-144319DiVA, id: diva2:1179103
Conference
ANZMAC 2017, Melbourne, Australia, December 4-6, 2017
Available from: 2018-01-31 Created: 2018-01-31 Last updated: 2019-06-20Bibliographically approved

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Mejtoft, ThomasSöderström, Ulrik

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf