Tracking entities in web archives
Marc Spaniol, Gerhard Weikum · 2012
Web-preservation organization like the Internet Archive not only capture the history of born-digital content but also reflect the zeitgeist of different time periods over more than a decade. This longitudinal data is a potential gold mine for researchers like sociologists, politologists, media and market analysts, or experts on intellectual property. The LAWA project (Longitudinal Analytics of Web Archive data) is developing an Internet-based experimental testbed for large-scale data analytics on Web archive collections. Its emphasis is on scalable methods for this specific kind of big-data analytics, and software tools for aggregating, querying, mining, and analyzing Web contents over long epochs. In this paper, we highlight our research on {\em entity-level analytics} in Web archive data, which lifts Web analytics from plain text to the entity-level by detecting named entities, resolving ambiguous names, extracting temporal facts and visualizing entities over extended time periods. Our results provide key assets for tracking named entities in the evolving Web, news, and social media.