The potential of machine mediation in the maintenance of public service media

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This production study argues predictive analytics (PA) and behavioral targeting (BT) will be useful for public service media (PSM). Whereas PA is the offering of digital content based on personal data, previous browsing behaviors, and user preferences, BT is the nuanced matching of content to audience segments. The topic is of critical importance for leaders of PSM, for media regulators and for audiences. The study draws on network and new media theory to provide context. The rationale for the study is the urgent need for PSM to begin using advanced digital production processes as mediation by machine is giving commercial digital firms a market advantage. An alternative PSM approach would benefit the quality of the public sphere. The use of PA and BT is considered in four cases: the websites of The Guardian and the BBC in the UK, and The Washington Post and CNN in the USA.
Original languageEnglish
Title of host publicationPublic Service Media Renewal: Adaptation to Digital Network Challenges
PublisherPeter Lang
Publication statusPublished - 31 Mar 2017

Keywords

  • big data
  • audience analysis
  • predictive analytics
  • privacy
  • public service media
  • behavioural targeting

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