Analytic Tools and Data

Policy makers and practitioners often generate solutions for mitigating or managing actual humanitarian crises using case-by-case methods that may not be informed by sufficient data. This is a result of unavailable data. Our goal is to support evidence-based policy creation. Therefore, one broad goal of our project is to complete the foundational work needed to develop analytic tools that can be used by practitioners and policy makers to understand, analyze and forecast forced migration in the future. We have been and will continue to develop tools for the broader community to access. Most of our work focuses on constructing variables from organic data sources, specifically social media and newspapers.

MDI Data Portal

To support social science researchers interested in using social media data, this data portal enables social scientists to generate structured variables using state of the art natural language processing, data mining, and machine learning. Our goal is to provide an easy to use infrastructure for social scientists to construct variables from organic data and blend them with other traditional variables. Our infrastructure supports sharing and combining these other types of more traditional, structured data. Over time, we will make our data mining and machine learning algorithms available and house case examples and templates for researchers new to social media data processing and analysis.

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Mapping Twitter Chatter in Iraq

The rapid expansion of the Islamic State (IS) across different parts of Iraq and the dramatic escalation of violence in late 2013 has caused millions of Iraqis to flee their homes. Here we attempt to understand the relationship between chatter and buzz on Twitter and the IS movement through Iraq. We use hundreds of millions of tweets related to IS to investigate chatter volume, sentiment of tweets involving IS related hashtags in both English and Arabic. The figures on this page describe this data and how it relates to movement.

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