Monday, October 21, 2019

Using SNA to model connections between, capabilities of, and common indicators among fighting forces in Syria


Research Question:
 àWhat can modeling fighter groups and their affiliates reveal about alliances in the Syrian conflict?

Why Social Network Analysis?
àThere has been much written about the eight-year long Syrian Civil War, particularly given recent operational decisions taken by U.S. President Donald Trump and Turkish President Erdogan. However, much of the media coverage fails to fully consider the chaotic mix of fighting forces on the ground in Syria. Pro-government forces include the Syrian army and a number of affiliated Shia militias, Russian forces and private military companies such as the Wagner Group[1], Iranian Revolutionary Guard Corps forces[2] and several allied proxy organizations including but not limited to Hezbollah. Opposition forces include the Free Syrian Army (FSA), the formerly U.S.-backed Syrian Democratic Forces (SDF) which are comprised mostly of Kurdish People’s Protection Unit (YPG) forces, the al-Qaeda derived group formerly known as Jabhat al-Nusra which has been re-branded into the Front for the Conquest of the Levant (JFS), and the Islamic State. The list of aforementioned groups is nowhere near comprehensive and involves many shifting inter-group dynamics such as fighters who move from one group to the next, and clashes between formerly allied groups. Additionally, Turkish forces have entered the mix by launching a recent incursion into northern Syria to establish a safe zone in currently SDF-held territory. Foreign nations funding various fighting groups in the Syria war include the U.S., Turkey, some European countries, Russia, Iran, Israel, Jordan, Saudi Arabia, Qatar, some other Gulf states, and more.[3] The Syrian War operational picture is deeply multi-faceted, and looking at data on each of these groups through social network analysis would facilitate greater discussion and deeper understanding of the complex situation. Furthermore, visual displays of the data may help reach a wider audience with more easily digestible information.

Data, Methodology, and Network Measures:
àThe network I would explore includes all of the groups involved in the Syrian War. I would collect data from well-respected think tanks, NGOs working on the ground, and government factsheets on which groups operate where and have what capabilities. Additionally, I would include data from a social network analysis conducted of Syrian rebel alliances, published in the Journal of Conflict Resolution.[4] Network measures would include questions such as the following:
·       Group type (foreign nation forces, militant group, terrorist group, paid mercenary group, proxy group, etc.)
·       Overall allegiance? (Pro-Assad, Opposition, other)
·       Professional fighting force? (Yes/No)
·       Holds territory? (Yes/No)
·       Size of territory held (with different ranges to select from):
·       Territory held in which governorates (there are 14 total):
·       Air power capabilities? (Yes/No)
·       Funded by:
·       Provided materiel support by:
·       Overlapping fighters with:
·       Major ethnic composition:`
·       Major religious composition:
NOTE: The above categories would be fully defined, with the understanding that there may be some debate or overlap in categories.

What will the SNA help you do?
àThis SNA would help answer questions such as which groups have air capabilities and hold territory in Aleppo Governorate, and allow for visual displays of important network connections such as groups funded by both Iran and Russia.
  


[1] Hauer, Neil. “The Rise and Fall of a Russian Mercenary Army.” Foreign Policy (blog). October 6, 2019. https://foreignpolicy.com/2019/10/06/rise-fall-russian-private-army-wagner-syrian-civil-war/.
[3] Laub, Zachary. “Who’s Who in Syria’s Civil War.” Council on Foreign Relations. April 28, 2017. https://www.cfr.org/backgrounder/whos-who-syrias-civil-war.
[4] Gade, Emily Kalah, Michael Gabbay, Mohammed M. Hafez, and Zane Kelly. “Networks of Cooperation: Rebel Alliances in Fragmented Civil Wars.” Journal of Conflict Resolution 63, no. 9 (October 2019): 2071–97. doi:10.1177/0022002719826234.

1 comment:

Christopher Tunnard said...

Solid discussion of SNA's relevance to your topic and of the attributes needed. Data search process you discuss seems reasonable. Good mention of the value of visual representations of these networks. What's missing is an explanation (not just a list) of the kind of networks you would need to answer your question about "revealing alliances." Financial nets? Faith nets? And what are the SNA measures you would use to support your conclusions?
Ben and RT