Infectious texts: Modeling text reuse in nineteenth-century newspapers

David A. Smith, Ryan Cordell, Elizabeth Maddock Dillon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Texts propagate through many social networks and provide evidence for their structure. We present efficient algorithms for detecting clusters of reused passages embedded within longer documents in large collections. We apply these techniques to analyzing the culture of reprinting in the United States before the Civil War. Without substantial copyright enforcement, stories, poems, news, and anecdotes circulated freely among newspapers, magazines, and books. From a collection of OCR'd newspapers, we extract a new corpus of reprinted texts, explore the geographic spread and network connections of different publications, and analyze the time dynamics of different genres.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE International Conference on Big Data, Big Data 2013
PublisherIEEE Computer Society
Pages86-94
Number of pages9
ISBN (Print)9781479912926
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 IEEE International Conference on Big Data, Big Data 2013 - Santa Clara, CA, United States
Duration: Oct 6 2013Oct 9 2013

Publication series

NameProceedings - 2013 IEEE International Conference on Big Data, Big Data 2013

Other

Other2013 IEEE International Conference on Big Data, Big Data 2013
Country/TerritoryUnited States
CitySanta Clara, CA
Period10/6/1310/9/13

Keywords

  • clustering algorithms
  • nearest neighbor searches

ASJC Scopus subject areas

  • Software

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