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We describe the design, implementation, and evaluation of EMBERS, an automated, 24x7 continuous system for forecasting civil unrest across 10 countries of Latin America using open source indicators such as tweets, news sources, blogs, economic indicators, and other data sources. Unlike retrospective studies, EMBERS has been making forecasts into the future(More)
Financial markets are quite sensitive to unanticipated news and events. Identifying the effect of news on the market is a challenging task. In this demo, we present Forex-foreteller (FF) which mines news articles and makes forecasts about the movement of foreign currency markets. The system uses a combination of language models, topic clustering, and(More)
As a surrogate data source for many real-world phenomena, social media such as Twitter can yield key insight into people's behavior and their group affiliations and memberships. As an event unfolds on Twitter, the language, hashtags, and vocabulary used to describe it evolves over time, so that it is difficult to a priori capture the composition of a social(More)
1 T here have been serious efforts over the past 40 years to use newspaper articles to create global-scale databases of events occurring in every corner of the world, to help understand and shape responses to global problems. Although most have been limited by the technology of the time (1) [see supplementary materials (SM)], two recent groundbreaking(More)
Infectious disease epidemics such as influenza and Ebola pose a serious threat to global public health. It is crucial to characterize the disease and the evolution of the ongoing epidemic efficiently and accurately. Computational epidemiology can model the disease progress and underlying contact network, but suffers from the lack of real-time and(More)
State-of-the-art event encoding approaches rely on sentence or phrase level labeling, which are both time consuming and infeasible to extend to large scale text corpora and emerging domains. Using a multiple instance learning approach, we take advantage of the fact that while labels at the sentence level are difficult to obtain, they are relatively easy to(More)
Storyline detection aims to connect seemly irrelevant single documents into meaningful chains, which provides opportunities for understanding how events evolve over time and what triggers such evolutions. Most previous work generated the storylines through unsupervised methods that can hardly reveal underlying factors driving the evolution process. This(More)
A quantitative analysis of tweets during the Ebola crisis reveals that lies, half-truths, and rumors can spread just like true news. A lthough Ebola isn't a new disease, the current outbreak in West Africa is believed to be more than three times worse than all previous ones in history combined. In addition, public health experts fear massive underreport-ing(More)
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