DocumentCode :
659526
Title :
Infectious texts: Modeling text reuse in nineteenth-century newspapers
Author :
Smith, David A. ; Cordell, Ryan ; Dillon, Elizabeth Maddock
Author_Institution :
Coll. of Comput. & Inf. Sci., Northeastern Univ. Boston, Boston, MA, USA
fYear :
2013
fDate :
6-9 Oct. 2013
Firstpage :
86
Lastpage :
94
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.
Keywords :
history; pattern clustering; publishing; text analysis; United States; cluster detection; documents; genre time dynamics; geographic spread; infectious texts; new corpus extraction; newspaper OCR; nineteenth-century newspapers; publication network connections; reprinting culture analysis; reused passages; social networks; text reuse modelling; Aggregates; Clustering algorithms; Heuristic algorithms; Indexing; Optical character recognition software; Social network services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data, 2013 IEEE International Conference on
Conference_Location :
Silicon Valley, CA
Type :
conf
DOI :
10.1109/BigData.2013.6691675
Filename :
6691675
Link To Document :
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