Collaborative annotation, analysis, and presentation interfaces for digital video

Abstract

Information quality corresponds to the degree of excellence in communicating knowledge or intelligence and encompasses aspects of validity, accuracy, reliability, bias, transparency, and comprehensiveness among others. Professional news, public relations, and user generated content alike all have their own subtly different information quality concerns. With so much recent growth in online video, it is also apparent that more and more consumers will be getting their information from online videos and that understanding the information quality of video becomes paramount for a consumer wanting to make decisions based on it.

This dissertation explores the design and evaluation of collaborative video annotation and presentation interfaces as motivated by the desire for better information quality in online video. We designed, built, and evaluated three systems: (1) Audio Puzzler, a puzzle game which as a by-product of play produces highly accurate time-stamped transcripts of video, (2) Videolyzer, a video annotation system designed to aid bloggers and journalists collect, aggregate, and share analyses of information quality of video, and (3) Videolyzer CE, a simplified video annotation presentation which syndicates the knowledge collected using Videolyzer to a wider range of users in order to modulate their perceptions of video information. We contribute to knowledge of different interface methods for collaborative video annotation and to mechanisms for enhancing accuracy of objective metadata such as transcripts as well as subjective notions of information quality of the video itself.