Name
Abstract | ||
|---|---|---|
Forecasting a domestic political crisis (DPC) in a country of interest is a very useful tool for social scientists and policy makers. A wealth of event data is now available for historical as well as prospective analysis. Using the publicly available GDELT dataset, we illustrate the use of frequent subgraph mining to identify signatures preceding DPCs, and the predictive utility of these signatures through both qualitative and quantitative results. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2615569.2615698 | WebSci |
Keywords | Field | DocType |
domestic political crises,gdelt,event forecasting,graph mining,data mining | Data science,Astronomy,Data mining,Graph,Computer science,Event data,Politics | Conference |
Citations | PageRank | References |
11 | 0.74 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yaser Keneshloo | 1 | 27 | 2.99 |
| Jose Cadena | 2 | 98 | 7.53 |
| Gizem Korkmaz | 3 | 98 | 11.10 |
| Naren Ramakrishnan | 4 | 1913 | 176.25 |