DYPLODOC: Dynamic Plots for Document Classification

TL;DR

This paper introduces DYPLODOC, a method for extracting dynamic plot features from TV show descriptions, facilitating narrative analysis and generation in natural language processing.

Contribution

The paper presents a novel feature extraction technique for plot dynamics and provides a new dataset of TV show plots with genre annotations.

Findings

Validated the plot dynamics extraction tool

Created a dataset of 13,000 TV show plots

Discussed applications in narrative analysis and generation

Abstract

Narrative generation and analysis are still on the fringe of modern natural language processing yet are crucial in a variety of applications. This paper proposes a feature extraction method for plot dynamics. We present a dataset that consists of the plot descriptions for thirteen thousand TV shows alongside meta-information on their genres and dynamic plots extracted from them. We validate the proposed tool for plot dynamics extraction and discuss possible applications of this method to the tasks of narrative analysis and generation.