Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 5:00 PM ET (12:00 - 21:00 UTC). We apologize for the inconvenience.
By Topic

A data-driven classification framework for conflict and instability analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Choi, K. ; Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Storrs, CT ; Pattipati, K.R. ; Asal, V.

Is it possible to identify and even forecast well in advance (6-12 months) the relative stability of a state to enable policy makers to successfully intervene? How does one acquire that understanding? One technique is to model and understand the social factors, which summarize the background conditions, attributes and performance factors of the country over time. The purpose of this paper is to: (1) present a generalized data-driven framework for conflict analysis and forecasting, (2) show that state-of-the-art pattern classification techniques provide significant improvements to forecasting accuracy, and (3) introduce classification problems arising in social sciences to the engineering community for further enhancement of analysis techniques. We evaluate the efficacy of our data-driven framework on macro-structural factors as relevant contributors to country instability, delineating the independent and dependent variables. The results demonstrate significant improvement over previous approaches in classification metrics of accuracy, precision, and recall.

Published in:

Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on

Date of Conference:

12-15 Oct. 2008