Skip to content

Content Analysis of 150 Years of British Periodicals

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)E457-E465
Number of pages9
JournalProceedings of the National Academy of Sciences
Volume114
Journal issue4
Early online date9 Jan 2017
DOIs
StatePublished - 24 Jan 2017

Abstract

Previous studies have shown that it is possible to detect macroscopic patterns of cultural change over periods of centuries by analyzing large textual time series, specifically digitized books. This method promises to empower scholars with a quantitative and data-driven tool to study culture and society, but its power has been limited by the use of data from books and simple analytics based essentially on word counts. This study addresses these problems by assembling a vast corpus of regional newspapers from the United Kingdom, incorporating very fine-grained geographical and temporal information that is not available for books. The corpus spans 150 years and is formed by millions of articles, representing 14% of all British regional outlets of the period. Simple content analysis of this corpus allowed us to detect specific events, like wars, epidemics, coronations, or conclaves, with high accuracy, whereas the use of more refined techniques from artificial intelligence enabled us to move beyond counting words by detecting references to named entities. These techniques allowed us to observe both a systematic underrepresentation and a steady increase of women in the news during the 20th century and the change of geographic focus for various concepts. We also estimate the dates when electricity overtook steam and trains overtook horses as a means of transportation, both around the year 1900, along with observing other cultural transitions. We believe that these data-driven approaches can complement the traditional method of close reading in detecting trends of continuity and change in historical corpora.

Research areas

  • artificial intelligence, digital humanities, computational history, data science, Culturomics

Download statistics

No data available

Documents

Documents

  • Full-text PDF (final published version)

    Rights statement: This is the final published version of the article (version of record). It first appeared online via National Academy of Sciences at http://doi.org/10.1073/pnas.1606380114. Please refer to any applicable terms of use of the publisher.

    Final published version, 9 MB, PDF-document

DOI

View research connections

Related faculties, schools or groups