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AI-driven contextual advertising: toward relevant messaging without personal data
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0001-8503-0118
2024 (English)In: Journal of Current Issues and Research in Advertising, ISSN 1064-1734Article in journal (Refereed) Epub ahead of print
Abstract [en]

In programmatic advertising, bids are increasingly based on knowledge of the surrounding media context. This shift toward contextual advertising is in part a counter-reaction to the current dependency on personal data, which is problematic from legal and ethical standpoints. The transition is accelerated by developments in artificial intelligence (AI), which allow for a deeper semantic analysis of the context and, by extension, more effective ad placement. We survey existing literature on the influence of context on the reception of an advertisement, focusing on three context factors: the applicability of the content and the ad, the affective tone of the content, and the involvement of the consumer. We then discuss how AI can leverage these priming effects to optimize ad placement through techniques such as reinforcement learning, data clustering, and sentiment analysis. This helps close the gap between the state of the art in advertising technology and the AI-driven targeting methodologies described in prior academic research.

Place, publisher, year, edition, pages
Routledge, 2024.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-224265DOI: 10.1080/10641734.2024.2334939ISI: 001209522500001Scopus ID: 2-s2.0-85192195055OAI: oai:DiVA.org:umu-224265DiVA, id: diva2:1857623
Available from: 2024-05-14 Created: 2024-05-14 Last updated: 2024-05-14

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fulltext(2117 kB)37 downloads
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Häglund, EmilBjörklund, Johanna

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CiteExportLink to record
Permanent link

Direct link
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