Category Archives: Datawork

Fragility and Transparency

When the OECD released their 2015 Fragility Report I remember looking at the penta-Venn Diagram of the different states of fragility and wondering why Afghanistan was not fragile in institutions, which was supposed to capture corruption among other governance issues. This question eventually led to a Monkey Cage post on my attempt to replicate their measures of fragility.

The 2015 OECD Fragility diagram with my edits

The OECD responded in a comment to the initial posting pointing out some problems with my replication while admitting certain errors. However, after a revised replication that incorporates those edits, all up on Github, I still get very different results.

I look forward to seeing OECD’s 2016 report as they have discussed some interesting revisions to their measure of fragility. Hopefully along with substantive improvements they will also incorporate improve their methodology especially by way of transparency. As the OECD continues to work with this data in order to provide a public good, the greatest good will come from being as public as possible.

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UCDPtools – R package for the Uppsala Conflict Data Program

I’m happy to introduce UCDPtools, an R package for accessing data from the Uppsala Conflict Data Program (UCDP). UCDPtools includes UCDPindex that makes it easy to move around the websites and codebooks for the 15 UCDP datasets and the function getUCDP() that loads the datasets into R and fixes obvious errors and variable names.

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Disaster Optimism: Phailin vs. Haiyan

In exploring the GDELT dataset around disasters, I found an interesting trend around the tragic Typhoon Haiyan.  Looking at events geolocated in the Philippines before and after the typhoon, I found a steep rise in the number of optimistic comments, clearly overtaking a rise in the number of pessimistic comments.

Haiyanloc_dailycountbycode

 

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Violence and NGO Attention with GDELT

I recently attended the PSU GDELT Hackathon where I got a chance to contribute to the R package GDELTtools. The experience inspired me to clean up and share my own explorations of GDELT. My colleague Anna Schrimpf presented a research plan looking at the incentive structure that NGOs like Amnesty International face when choosing which issues to focus on. I found her research agenda fascinating and wondered if it could be applied to different types of conflict.

To check, I took the three UCDP datasets on annual casualties from (1) battles related to civil or interstate war, (2) one-sided government attacks on civilians, and (3) violence between non-state actors from 1989 and 2011 and plotted total fatalities against the count of Media-reported NGO actions using GDELT. For each country-year, I count the number of actions by Amnesty International, Human Rights Watch, Oxfam, or the Red Cross that target an actor of that country in that year. The resulting plot below contains 2500 points spread across 170 countries.

NGOoutliersmed

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