This thesis involves parsing document-based reports from the United States Human Rights Reports and rating the human practices for various countries based on the CIRI (Cingranelli-Richards) Human Rights Data Project dataset. The United States Human Rights Reports are annual reports that cover internationally recognized human rights practices regarding individual, civil, political, and worker rights. Students, scholars, policymakers, and analysts used the CIRI data for practical and research purposes. CIRI analyzed the annual reports from 1981 to 2011 and then stopped releasing the dataset for any further years, but a possible reason is due to the manual process of scouring the Human Rights Reports and then rating each human rights practice for each country. This manual process provides a solid foundation for creating a new automated process. The automated process uses the rating values provided by CIRI in the 1981-2011 dataset as expected values to evaluate the accuracy of the rating process.
To transition to an automated process, the General Architecture for Text Engineering (GATE) application is used. GATE is an open source project used for developing solutions for text processing. GATE is used in conjunction with the coding schemes provided within the CIRI Coding Manual to create an automated ratings process. The CIRI Coding Manual uses qualitative and quantitative criteria. The original and automated ratings are evaluated using GATE’s Annotation Diff Tool to get the
F-measure for every country in the dataset. The evaluation cases range between 1999 and 2011 because those are the only years included in both the CIRI dataset and the Human Rights Reports. The F-measure results are more accurate when quantitative criteria is used to rate human rights practices. The primary contribution of this thesis is a method for automating each country’s human practice ratings so that the purpose of the CIRI project can be continued.
| Identifer | oai:union.ndltd.org:unf.edu/oai:digitalcommons.unf.edu:etd-1851 |
| Date | 01 January 2018 |
| Creators | Joiner, Joshua M |
| Publisher | UNF Digital Commons |
| Source Sets | University of North Florida |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | UNF Graduate Theses and Dissertations |
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