|dc.description.abstract||This project has at least two facets to it: (1) advancing the algorithms in the sub-field of bibliometrics often referred to as "text mining" whereby hundreds of thousands of documents (such as journal articles) are scanned and relationships amongst words and phrases are established and (2) applying these tools in support of the Explorations in Cyber International Relations (ECIR) research effort. In international relations, it is important that all the parties understand each other. Although dictionaries, glossaries, and other sources tell you what words/phrases are supposed to mean (somewhat complicated by the fact that they often contradict each other), they do not tell you how people are actually using them.
As an example, when we started, we assumed that "cyberspace" and "cyber space" were essentially the same word with just a minor variation in punctuation (i.e., the space, or lack thereof, between "cyber" and "space") and that the choice of the punctuation was a rather random occurrence. With that assumption in mind, we would expect that the taxonomies that would be constructed by our algorithms using "cyberspace" and "cyber space" as seed terms would be basically the same. As it turned out, they were quite different, both in overall shape and groupings within the taxonomy.
Since the overall field of cyber international relations is so new, understanding the field and how people think about (as evidenced by their actual usage of terminology, and how usage changes over time) is an important goal as part of the overall ECIR project.||en_US