TY - JOUR
T1 - Understanding Shifting Triadic Relationships in the Al-Qaeda/ISIS Faction Ecosystem
AU - Bellutta, Daniele
AU - Chen, Youdinghuan
AU - Gartenstein-Ross, Daveed
AU - Pulice, Chiara
AU - Subasic, Anja
AU - Subrahmanian, V. S.
N1 - Funding Information:
Manuscript received January 27, 2020; revised August 29, 2020; accepted August 31, 2020. Date of publication September 23, 2020; date of current version January 13, 2021. This work was supported in part by Office of Naval Research (ONR) under Grant N00014-16-1-2918. (Corresponding author: V. S. Subrahmanian.) Daniele Bellutta, Youdinghuan Chen, Chiara Pulice, Anja Subasic, and V. S. Subrahmanian are with Dartmouth College, Hanover, NH 03755 USA (e-mail: daniele.bellutta.gr@dartmouth.edu; youdinghuan. chen.gr@dartmouth.edu; chiara.pulice@dartmouth.edu; anja.subasic.gr@ dartmouth.edu; vs@dartmouth.edu).
Publisher Copyright:
© 2014 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - We propose and investigate 14 hypotheses linking changes in the intensity of relationships between two factions in the Al-Qaeda/ISIS (AQ/ISIS) (ecosystem to future changes in other relationships involving one of those two factions. Using a novel 28-year data set of relationships between factions of Al-Qaeda and the Islamic State (including their predecessor organizations) encoded as a time series of 267 signed weighted networks, we identify triangles of any set of connected factions $(u,v,z)$ and develop hypotheses capturing how the intensity of relationships between two factions $u,v$ changes when the relationship between either factions $z,u$ or factions $z,v$ changes. We investigate how the strength of these relationships changes in the short term (less than two years), medium term (two to four years), and long term (five to ten years). Surprisingly, we show that AQ/ISIS triangles that are not in balance (according to the balance theory) are unlikely to move toward balance as suggested by the balance theory, but those that are in balance will likely stay balanced (as suggested by the balance theory). These findings provide better insight into the inner workings and complex dynamics that shape the AQ/ISIS competition worldwide. They are also relevant to future developments in global jihadism, as new factions may emerge that seek to gain affiliative market share in the jihadist world at the expense of more established organizations.
AB - We propose and investigate 14 hypotheses linking changes in the intensity of relationships between two factions in the Al-Qaeda/ISIS (AQ/ISIS) (ecosystem to future changes in other relationships involving one of those two factions. Using a novel 28-year data set of relationships between factions of Al-Qaeda and the Islamic State (including their predecessor organizations) encoded as a time series of 267 signed weighted networks, we identify triangles of any set of connected factions $(u,v,z)$ and develop hypotheses capturing how the intensity of relationships between two factions $u,v$ changes when the relationship between either factions $z,u$ or factions $z,v$ changes. We investigate how the strength of these relationships changes in the short term (less than two years), medium term (two to four years), and long term (five to ten years). Surprisingly, we show that AQ/ISIS triangles that are not in balance (according to the balance theory) are unlikely to move toward balance as suggested by the balance theory, but those that are in balance will likely stay balanced (as suggested by the balance theory). These findings provide better insight into the inner workings and complex dynamics that shape the AQ/ISIS competition worldwide. They are also relevant to future developments in global jihadism, as new factions may emerge that seek to gain affiliative market share in the jihadist world at the expense of more established organizations.
KW - Balance theory
KW - counterterrorism
KW - social network analysis
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U2 - 10.1109/TCSS.2020.3022586
DO - 10.1109/TCSS.2020.3022586
M3 - Article
AN - SCOPUS:85099582005
VL - 7
SP - 1423
EP - 1434
JO - IEEE Transactions on Computational Social Systems
JF - IEEE Transactions on Computational Social Systems
SN - 2329-924X
IS - 6
M1 - 9204761
ER -