TY - GEN
T1 - Forecasting country stability in North Africa
AU - Banaszak, Steven
AU - Bowman, Elizabeth
AU - Dickerson, John P.
AU - Subrahmanian, V. S.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/4
Y1 - 2014/12/4
N2 - We develop a novel approach to predict certain type of stability events (battles, battles won by a government, riots/protests, violence against civilians) in countries by monitoring the content of a mix of traditional news, blog, and social media data. Specifically, we show that by monitoring sentiment on both pro-and anti-government entities within a country, even with a relative paucity of longitudinal data (36 time points), we can predict these stability related events with just over 80% classification accuracy. We report on our methods, together with a description of a prototype system called Sentibility that tracks country stability related events. In addition, we cast light on the key entities, sentiments on whom were correlated strongly (positively or negatively) by both Pearson and Spearman correlation coefficients, with such stability events in 3 countries: Egypt, Morocco, and Sudan.
AB - We develop a novel approach to predict certain type of stability events (battles, battles won by a government, riots/protests, violence against civilians) in countries by monitoring the content of a mix of traditional news, blog, and social media data. Specifically, we show that by monitoring sentiment on both pro-and anti-government entities within a country, even with a relative paucity of longitudinal data (36 time points), we can predict these stability related events with just over 80% classification accuracy. We report on our methods, together with a description of a prototype system called Sentibility that tracks country stability related events. In addition, we cast light on the key entities, sentiments on whom were correlated strongly (positively or negatively) by both Pearson and Spearman correlation coefficients, with such stability events in 3 countries: Egypt, Morocco, and Sudan.
KW - Sentiment analysis
KW - forecasting stability events
UR - http://www.scopus.com/inward/record.url?scp=84920279647&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84920279647&partnerID=8YFLogxK
U2 - 10.1109/JISIC.2014.60
DO - 10.1109/JISIC.2014.60
M3 - Conference contribution
AN - SCOPUS:84920279647
T3 - Proceedings - 2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014
SP - 304
EP - 307
BT - Proceedings - 2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014
Y2 - 24 September 2014 through 26 September 2014
ER -
