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Automated event extraction from free text remains an open problem, particularly when the goal is to identify all relevant events. Manual extraction is currently the only alternative for comprehensive and reliable extraction. Therefore, it is required to have a system that can comprehensively extract events reported in news articles (high recall) and is also scalable enough to handle a large number of articles. In this dissertation, we explore various methods to develop an event extraction system that can mitigate these challenges. We primarily investigate three major problems related to event extraction as follows. (i) What are the strengths and weaknesses of the automated event extractors? A thorough understanding of what can be automated with high success and what leads to common pitfalls is crucial before we could develop a superior event extraction system. (ii) How can we build a hybrid event extraction system that can bridge the gap between manual and automated event extraction? Hybrid extraction is a semi-automated approach that uses an ecosystem of machine learning models along with a carefully designed user interface for extracting events. Since this method is semi-automated it also requires a meticulous understanding of user behavior in order to identify tasks that humans can perform with ease while diverting the more tedious task to the machine learning methods (iii) Finally, we explore methods for displaying extracted events that could simplify the analytical and inference generation processes for an analyst. We particularly aim to develop visualizations that would allow analysts can perform macro and micro level analysis of significant societal events. / Ph. D. / News articles provide information about who did what to whom, when, where, and why. Extracting this structured information from news articles can allow scientific evaluation of widely believed information. However, curating these databases of structured information is not a trivial task. Currently there are two main approaches: manual and automated. Manually curation is not scalable due to labor costs: adding more humans to perform analysis is prohibitively expensive and time consuming. The alternative approach is ‘Automated Extraction’, wherein, machine learning algorithms extract events on their own without any human assistance. Even though this approach can easily scale to work with a large number of articles, it frequently misclassifies events. In this dissertation, we present EMBERS AutoGSR, a framework for comprehensively extracting ‘protest’ events reported in news articles using Hybrid Event Extraction. In the hybrid approach, we use an ecosystem of Filtering, Ranking, and Recommendation models to determine if an article is reporting a protest and, if so, proceed to identify and encode specific characteristics of the event, such as who protested when, where and why? These extracted events are then displayed on an interactive web-based interface that allows manual validation. This manual validation, in turn, helps the automated event extractors learn and evolve from user feedback and error correction. The interface is carefully designed with an aim to minimize the manual effort required for user validation, thereby making it feasible and viable to work with a large number of articles. EMBERS AutoGSR operated 24x7 for a year from October 2015 through September 2016, during which it extracted protest events from news articles that were collected from 19 countries across 8 languages. These extracted events were validated by 12 subject matter experts. The system was evaluated by an independent third party, MITRE corporation. They compared EMBERS AutoGSR events with events that were manually extracted by their team of political scientists. AutoGSR achieved a recall of 0.82 out of 1, and reduced the manual effort required for event extraction by 72%, thereby making the system extremely reliable and scalable.

no / This book is an invitation to reflect on the dangers that threaten the stability, security and world peace. The authors point to climate change, competition for natural resources, the gap between rich and poor and the proliferation of military technologies as factors capable of triggering violent conflict, civil unrest and destabilization of international order in the near future if immediate measures are not taken. From a rigorously researched analysis, then present strategies and sustainable alternatives to build a more cooperative, fair and conscious future. A book that promises to change the way you view the world.

Between 1991 and 2000, Sierra Leone experienced massive state and economic decline amidst a brutal civil war. In a country that is minerally wealthy, but ruled by a corrupt and predatory government, a `revolutionary¿ movement known as the RUF emerged, terrorising the civilian population and profiting from the unsecured diamond industry. The classic causes given for Sierra Leone¿s state collapse and consequent civil war have in large centred around the adverse effects of colonialism, civil unrest due to rampant governmental kleptocracy, and regional conflict spillover. However, the multiplicity of actors in Sierra Leone and the complexity of the environment demonstrate that the ten year civil war revolved predominantly around the country¿s highly lucrative diamonds. Indoctrinated in Qadafi¿s Libya and trained by Taylor¿s NPFL rebels in Liberia, the RUF insurgency created links through Charles Taylor to international criminals such as weapon¿s dealer Victor Bout, and international terrorists including al Qaeda. In just a few years Sierra Leone attained the dubious distinction of being one of the most globalised informal and illegal economies in the world. To the backdrop of Sierra Leone¿s collapsed state, economic vacuum and brutal civil war, and within the context of contemporary economic globalisation and an international `War on Terror¿, this paper discusses the local, regional and international levels of economic exploitation throughout the wartime period, and highlights how informal economies are inherently prone to large scale criminal predation.

As the Honduran presidential election of 2017 approaches, the world of 17-year-old Libertad Morazán gets louder and faster. Protests roar in every corner of Tegucigalpa. Mamí and Abuela work longer hours. Maynor, Libertad's older brother, sneaks out more than ever, carrying the dangerous secrets of a student-led movement against the government. The world only seems to slow down around Camila, Libertad's long-time friend who lately seems to hold Libi's hand and eyes two seconds too long. Libi and Cami's friendship always toed the line of something more— or did, at least, before Libertad's phone stopped working and their communication got cut to school-hours only. Libi can't help but think this is part of why Camila starts officially dating Pablo, the soccer team captain. If this isn't enough reason to desperately need her phone back, Libertad has just discovered the power of social media to speak against the conditions that keep her family— her country— in a permanent state of exhaustion and mourning. Using an anonymous Instagram account, Libertad posts short but charged poems denouncing the injustice local news outlets ignore. She finds an audience that resonates with her, but people who speak out in Honduras are rarely able to do so for long. Libertad knows this. Getting her phone back comes with a price, as both her political poetry and secret romance risk being exposed to Mamí and Abuela—the women who have sacrificed everything to raised her. The pillars of her life. In the midst of civil unrest, Libertad learns of the power and heartbreak in queerness, family, and activism. / Master of Fine Arts / Libertad is a young-adult novel.

Includes supplemental material. / Disaster relief operations, such as the 2005 Tsunami and Hurricane Katrina, and wartime operations, such as Operation Enduring Freedom and Operation Iraqi Freedom, have identified the need for a standardized command and control system interoperable among Joint, Coalition, and Interagency entities. The Systems Engineering Analysis Cohort 9 (SEA-9) Rapid Response Command and Control (R2C2) integrated project team completed a systems engineering (SE) process to address the military’s command and control capability gap. During the process, the R2C2 team conducted mission analysis, generated requirements, developed and modeled architectures, and analyzed and compared current operational systems versus the team’s R2C2 system. The R2C2 system provided a reachback capability to the Regional Combatant Commander’s (RCC) headquarters, a local communications network for situational assessments, and Internet access for civilian counterparts participating in Humanitarian Assistance/Disaster Relief operations. Because the team designed the R2C2 system to be modular, analysis concluded that the R2C2 system was the preferred method to provide the RCC with the required flexibility and scalability to deliver a rapidly deployable command and control capability to perform the range of military operations.