Generation of views of TV content using TV viewers' perspectives expressed in live chats on the web

Abstract

We propose a method of generating views of TV programs based on viewer's perspectives expressed in live chats on the Web. Important scenes in a program and responses by particular viewers can be extracted efficiently by statistically computing and/or recognizing live chat data obtained in sync with the broadcast content. We show that by using the computed results, views can be generated that indicate the momentum of reactions by viewers and scenes of interest to particular viewers whose preferences are similar to those of the viewer, etc. This is a new way of viewing TV content from various perspectives.