Lost in visualization: using quantitative content analysis to identify, measure, and categorize political cartographic manipulations.
2010-02
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Lost in visualization: using quantitative content analysis to identify, measure, and categorize political cartographic manipulations.
Authors
Published Date
2010-02
Publisher
Type
Thesis or Dissertation
Abstract
All maps are biased. Yet, some maps appear more biased than others. Though we have enough research to answer how and why maps can be used as tools for political argumentation, geographers have been remiss in scrutinizing how and why some maps are presumed to be more biased than others. I argue the reason for this lapse is primarily due to methodological shortcoming. This dissertation is an attempt to establish a new methodological framework with which we can begin answering fundamental questions that have been ignored thus far in the literature on politically motivated cartography. First, is it possible to quantify and compare different map manipulations found on overtly political maps? Second, are there any techniques of cartographic and visual manipulation that make maps produced for political purposes appear more subjective or objective? If so, how do these techniques correlate or cluster with one another on maps? Finally, can we establish a non-anecdotal categorical framework that will allow us to compare the type of cartographic manipulations found in a sample of maps with those found in other maps? I use quantitative content analysis to answer these research questions while testing the method's applicability to increasing our understanding of how maps are used to make political arguments.
Description
University of Minnesota Ph.D. dissertation. February 2010. Major: Geography. Advisor: Dr. Robert McMaster. 1 computer file (PDF); xviii, 252 pages, appendices 1-2. Ill. maps (some col.)
Related to
Replaces
License
Collections
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Suggested citation
Muehlenhaus, Ian Alexander. (2010). Lost in visualization: using quantitative content analysis to identify, measure, and categorize political cartographic manipulations.. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/59585.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.