Infectious texts: modeling text reuse in nineteenth-century newspapers.

Title:
Infectious texts : modeling text reuse in nineteenth-century newspapers
Creator:
Smith, David A. (Author)
Cordell, Ryan (Author)
Dillon, Elizabeth Maddock (Author)
Publisher:
IEEE, October 06, 2013
Type of resource:
Text
Genre:
Articles
Format:
electronic
Digital origin:
born digital
Abstract/Description:
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.
Comments:
Authors' manuscript of a paper presented at IEEE BigData 2013: Workshop on Big Data and the Humanities (Santa Clara, Calif., October 6-9, 2013). http://cci.drexel.edu/bigdata/bigdata2013/index.htm
Subjects and keywords:
clustering algorithms
nearest neighbor searches
text mining
digital humanities
newspapers
Other Arts and Humanities
Theory and Algorithms
Permanent Link:
http://hdl.handle.net/2047/d20004858

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