Extracting Event-Centric Document Collections from Large-Scale Web Archives

TL;DR

This paper introduces a focused extraction algorithm that efficiently retrieves event-centric document collections from large-scale web archives, aiding researchers in social sciences, history, and journalism.

Contribution

The paper presents a novel focused extraction method tailored for large web archives to access event-specific collections beyond individual documents.

Findings

Effective extraction of event-centric collections from 19-year German Web archive

Method works across different event types

Enables targeted access to large-scale web data

Abstract

Web archives are typically very broad in scope and extremely large in scale. This makes data analysis appear daunting, especially for non-computer scientists. These collections constitute an increasingly important source for researchers in the social sciences, the historical sciences and journalists interested in studying past events. However, there are currently no access methods that help users to efficiently access information, in particular about specific events, beyond the retrieval of individual disconnected documents. Therefore we propose a novel method to extract event-centric document collections from large scale Web archives. This method relies on a specialized focused extraction algorithm. Our experiments on the German Web archive (covering a time period of 19 years) demonstrate that our method enables the extraction of event-centric collections for different event types.