Stories From the Past Web

TL;DR

This paper explores methods for extracting various narrative stories from web archive collections, providing models and case studies to enhance understanding and interpretation of large web data sets.

Contribution

It introduces new models and case studies for generating different types of stories from web archives, aiding comprehension of large collections.

Findings

Multiple story types can be generated from web archives

Models and definitions for story extraction are proposed

Case studies demonstrate practical applications

Abstract

Archiving Web pages into themed collections is a method for ensuring these resources are available for posterity. Services such as Archive-It exists to allow institutions to develop, curate, and preserve collections of Web resources. Understanding the contents and boundaries of these archived collections is a challenge for most people, resulting in the paradox of the larger the collection, the harder it is to understand. Meanwhile, as the sheer volume of data grows on the Web, "storytelling" is becoming a popular technique in social media for selecting Web resources to support a particular narrative or "story". There are multiple stories that can be generated from an archived collection with different perspectives about the collection. For example, a user may want to see a story that is composed of the key events from a specific Web site, a story that is composed of the key events of the story regardless of the sources, or how a specific event at a specific point in time was covered by different Web sites, etc. In this paper, we provide different case studies for possible types of stories that can be extracted from a collection. We also provide the definitions and models of these types of stories.