On March 29, 2017, after ten years with a Presidential moratorium on metallic mining in the country, the Salvadoran legislature voted to permanently ban the practice. Based on semi-structured interviews with activists, academics, and journalists, this study builds on the literature explores the contributions of the Salvadoran diaspora in Canada to the passage of the moratorium, and ultimately the ban. I discuss numerous types of contributions: coalition building involving various allies, communication and education initiatives, taking a position as members of the diaspora, and engagements with politicians in both Canada and El Salvador. I provide further context to the case by discussing both contextual elements and mobilization strategies relating to the mining justice movement in El Salvador, contextual elements that help make sense of the engagements of the Salvadoran diaspora in Canada in the movement, and challenges Salvadoran Canadians encountered while engaging in the movement. I conduct my analysis in three parts. The first outlines contributions to the transnationalism literature, the second details the results of a discourse analysis of my interview transcripts, and the third sketches contributions to the framing literature.

The ever-increasing use of the internet by terrorist groups as a platform for the dissemination of radical, violent ideologies is well documented. The internet has, in this way, become a breeding ground for potential lone-wolf terrorists; that is, individuals who commit acts of terror inspired by the ideological rhetoric emitted by terrorist organizations. These individuals are characterized by their lack of formal affiliation with terror organizations, making them difficult to intercept with traditional intelligence techniques. The radicalization of individuals on the internet poses a considerable threat to law enforcement and national security officials. This new medium of radicalization, however, also presents new opportunities for the interdiction of lone wolf terrorism. This dissertation is an account of the development and evaluation of an information technology (IT) framework for detecting potentially radicalized individuals on social media sites and Web fora. Unifying Collective Action Framing Theory (CAFT) and a radicalization model of lone wolf terrorism, this dissertation analyzes a corpus of propaganda documents produced by several, radically different, terror organizations. This analysis provides the building blocks to define a knowledge model of terrorist ideological framing that is implemented as a Semantic Web Ontology. Using several techniques for ontology guided information extraction, the resultant ontology can be accurately processed from textual data sources. This dissertation subsequently defines several techniques that leverage the populated ontological representation for automatically identifying individuals who are potentially radicalized to one or more terrorist ideologies based on their postings on social media and other Web fora. The dissertation also discusses how the ontology can be queried using intuitive structured query languages to infer triggering events in the news. The prototype system is evaluated in the context of classification and is shown to provide state of the art results. The main outputs of this research are (1) an ontological model of terrorist ideologies (2) an information extraction framework capable of identifying and extracting terrorist ideologies from text, (3) a classification methodology for classifying Web content as resonating the ideology of one or more terrorist groups and (4) a methodology for rapidly identifying news content of relevance to one or more terrorist groups.