New Methods of Analysis of Narrative and Semantics in Support of Interactivity

TL;DR

This paper introduces new analytical methods for narrative and semantic analysis to enhance interactivity in multimedia content, leveraging mathematical algorithms for data clustering and supporting collaborative problem-solving.

Contribution

It presents novel analytical techniques for narrative and semantics that facilitate interactivity and cross-sector content re-use, based on advanced data clustering algorithms.

Findings

Algorithms support varied story-lines and interactivity

Facilitate cross-sector content re-use

Enable collective, distributed problem-solving

Abstract

Our work has focused on support for film or television scriptwriting. Since this involves potentially varied story-lines, we note the implicit or latent support for interactivity. Furthermore the film, television, games, publishing and other sectors are converging, so that cross-over and re-use of one form of product in another of these sectors is ever more common. Technically our work has been largely based on mathematical algorithms for data clustering and display. Operationally, we also discuss how our algorithms can support collective, distributed problem-solving.