An annotation model for making sense of information quality in online video

ABSTRACT

Making sense of the information quality of online media including things such as the accuracy and validity of claims and the reliability of sources is essential for people to be well-informed. We are developing Videolyzer to address the challenge of information quality sense-making by allowing motivated individuals to analyze, collect, share, and respond to criticisms of the information quality of online political videos and their transcripts. In this paper specifically we present a model of how the annotation ontology and collaborative dynamics embedded in Videolyzer can enhance information quality.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.4 Hypertext/Hypermedia

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.3 Group and Organization Interfaces

General Terms:
Design, Human Factors

Keywords:
collaborative annotation, information quality, journalism, tagging, video analysis