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