Computational Properties of Fiction Writing and Collaborative Work
This work addresses the need for advanced computational support in fiction writing and collaborative editing, though it appears incremental by building on existing research in data mining and visualization.
The paper tackles the problem of analyzing narrative semantics, pace, and rhythm in fiction writing beyond word-level tools, using data mining to visualize these aspects, with applications demonstrated in two related domains.
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.