TL;DR
This paper explores how digital archives, when analyzed with advanced data techniques, reveal insights into topics, themes, and key authors over time, based on extensive records from The Guardian and the British National Bibliography.
Contribution
It introduces a comprehensive approach combining social network analysis, coincidence analysis, data reduction, and visual analytics to analyze large digital archives.
Findings
Identification of main themes and topics over time
Recognition of leading authors and publishers
Insights into publication trends from large datasets
Abstract
Digital archives contribute to Big data. Combining social network analysis, coincidence analysis, data reduction, and visual analytics leads to better characterize topics over time, publishers' main themes and best authors of all times, according to the British newspaper The Guardian and from the 3 million records of the British National Bibliography.
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