Computational Properties of Fiction Writing and Collaborative Work

TL;DR

This paper explores the computational aspects of fiction writing and collaboration, emphasizing semantic visualization and data mining to enhance narrative analysis and support collaborative storytelling.

Contribution

It introduces advanced methods for visualizing narrative semantics, pace, and rhythm, extending beyond traditional word-level tools to support collaborative fiction writing.

Findings

Development of visualization techniques for narrative analysis

Application of data mining to real-world collaborative writing scenarios

Enhanced tools for understanding story structure and pacing

Abstract

From the earliest days of computing, there have been tools to help shape narrative. Spell-checking, word counts, and readability analysis, give today's novelists tools that Dickens, Austen, and Shakespeare could only have dreamt of. However, such tools have focused on the word, or phrase levels. In the last decade, research focus has shifted to support for collaborative editing of documents. This work considers more sophisticated attempts to visualise the semantics, pace and rhythm within a narrative through data mining. We describe real life applications in two related domains.