Identifying and Visualizing Semantic Indicators of Emerging Refugee Risks


Long before refugee crises emerge, there is a large amount of anecdotal and research data (mostly unstructured) that provides insight into devolving human conditions. The information is rarely in a single language, in a consistent form or published on well read sites. This information is very challenging to identify using traditional search techniques and structured data analytics as it is often sparse, inconsistent and not yet ‘popular’. Using data plugins that connect to more remote sites, evolving semantic models that identify increases in velocity of refugee indicators, powerful text analytics and associated visualizations, users can identify threatened regions and possible mitigating actions. This presentation discusses and demonstrates emerging refugee threat models, associated analytics and high impact visualizations in Savanna, a web based all source analysis solution.