Publication
Title
Detecting contrast patterns in newspaper articles by combining discourse analysis and text mining
Author
Abstract
Text mining aims at constructing classification models and finding interesting patterns in large text collections. This paper investigates the utility of applying these techniques to media analysis, more specifically to support discourse analysis of news reports about the 2007 Kenyan elections and post-election crisis in local (Kenyan) and Western (British and US) newspapers. It illustrates how text mining methods can assist discourse analysis by finding contrast patterns which provide evidence for ideological differences between local and international press coverage. Our experiments indicate that most significant differences pertain to the interpretive frame of the news events: whereas the newspapers from the UK and the US focus on ethnicity in their coverage, the Kenyan press concentrates on sociopolitical aspects.
Language
English
Source (journal)
Pragmatics / International Pragmatics Association. - Wilrijk
Publication
Wilrijk : 2011
ISSN
1018-2101
Volume/pages
21:4(2011), p. 647-683
ISI
000299721500007
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 05.03.2012
Last edited 24.06.2017
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