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Digging into Human Rights Documents
The objective of this research project is to develop a software toolset that mines a large set of unstructured text archives of human rights abuses. The software tool is designed to discover stories of hidden human rights victims and unidentified perpetrators. These stories do not exist in one document, but as fragments of text embedded across multiple documents. Thus, these stories can be identified only when reading across a large number of related documents. The current approach of manually reading to identify such stories is extremely tedious, time consuming, unsystematic, and error-prone. Human readers find it difficult to correlate the identity of victims, perpetrators, and details of abuse that reside across multiple documents. Thus, success of this project has large implications for the human rights community, as currently there is a lack of adequate tool support for automatically reading and identifying stories from large-scale unstructured text document sets.
This project received 2011 Digging Into Data Challenge Award. US team is funded by the National Science Foundation (NSF), Award no.: #1209172 and Canadian team is funded by Social Sciences and Humanities Research Council (SSHRC). US team is led by Dr. Ben Miller from Georgia State University and the Canadian team is led by Dr. Lu Xiao from Western University. I am co-PI for the US team and UNF is sub-recipient for this award.
The project team includes faculty, graduate students, and industry partners in the US and Canada with expertise in text analytics, natural language processing, qualitative research methods, rhetoric, human rights testimony, archival practice and theory, interface research and design, and complex software development.