autogsr_system

EMBERS AutoGSR: Automated Event Extraction from News Articles

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EMBERS AutoGSR is a novel, web based framework that generates a comprehensive database of validated civil unrest events using minimal human effort. AutoGSR is a deployed system for the past 6 months that is continually processing data 24X7 in an automated fashion. The system extracts civil unrest events of type “who protested where, when and…

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DMAP System

DMAP: Data Aggregation and Presentation Framework

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DMAP (Data Mining and Automation for Platforms) is an online framework that presents a wide variety of official data, news and information about companies. It is developed with an aim to act as a one-stop platform for displaying everything official related to a company and its competitors. It aggregates data from the following sources: Bing…

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Embers

EMBERS: Civil Unrest Forecasting using Open Source Data

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EMBERS is a fully automated 24×7 cloud hosted system, that generates forecasts for significant societal events using open source data including: tweets, Facebook pages, news articles, blog posts, Google search volume, Wikipedia, meteorological data, economic and financial indicators, coded event data, online restaurant reservations (Open Table), satellite imagery. EMBERS is sponsored by a contract for…

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Currency Exchange Rate Prediction

Forex-foreteller (FF): Currency Exchange Rates Determiner

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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 sentiment…

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Rumor Detection on Twitter

Modeling of Rumor Spreading on Twitter

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Characterizing information diffusion on social platforms like Twitter enables us to understand the properties of underlying media and model communication patterns. As Twitter gains in popularity, it has also become a venue to broadcast rumors and misinformation. We use epidemiological models to characterize information cascades in twitter resulting from both news and rumors. Specifically, we…

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merseyside

Crime Hotspot Tracking and Geo-Spatial Analysis

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Crime prediction is a topic of significant research across the fields of criminology, data mining, city planning, law enforcement, and political science. Crime patterns exist on a spatial level; these patterns can be grouped geographically by physical location, and analyzed contextually based on the region in which crime occurs. This project identifies a mechanism to parameterize street-level crime, localize crime hotspots,…

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