ABSTRACT
This chapter examines whether patterns of convergence and emergence explain radicalization in an epistemic network of the Arab Spring. A hypothetical Islamic network is coded in NetLogo to create patterns of spatial grouping determined by agent adaptability to their peers in a Moore neighborhood. Influence rate and employment determine the spatial distribution of the agents. Convergence rather than emergence is revealed as the driver of network clustering and hence explains radicalization among the majority of the agent subset. 9.1 Introduction
The events marked by the first political demonstration in Sidi Bouzid in Tunisia on December 18, 2010, following the self-immolation by Mohamed Bouazizi provide social science an opportunity for
testing the correlation between tipping points and social protests. The so-called Arab Spring opens the door for examining the links between tipping points and contextual drivers. A tipping point is a type of change in a system’s dynamic that leads to large-scale transformation. Contextual tipping points are a series of micro changes that cause a shift in the macro outcome. In this agent-based model, I measure the effect of unemployment on agent actors and suggest why unemployment, especially among the youth population, was a key driver that triggered a tipping point in the Arab Spring.aThis chapter attempts to explain the behavior in social networks during the Arab Spring that caused the breakdown of two longterm tyrannies in the Middle East, that of Zine el Abidine Ben Ali on January 14, 2011, and Hosni Mubarak on February 11, 2011. This agent-based model is designed to capture the dynamics of how groups function as collective vehicles of belief propagation, and to reveal the conditions under which informal substructure can change from being system supporting to being system destabilizing, and what the relationship is between belief diffusion and social insurgency. In Sections 9.4 and 9.4.1, I reference existing social science theories of collective action that are applicable to describe the social context of the Arab Spring.Existing theories in computational dynamics do not hold in the simulated environment that I describe in this chapter as far as telling us what led to the political transitions in the Arab Spring [2,4,5,10,12,17]. Some of these theories state that sight radius is a factor [12]. Sight radius in computational dynamics describes the distance between agents in a computational population set. I offer an alternative explanation for a mechanism that causes social unrest to reach a tipping point that leads to political change in society.The 2011 uprisings in the Middle East demonstrated that there were many factors in society that were on the verge of tipping into unrest for many years. One of these primary factors is the so-called aThe term “Arab Spring” appeared in media to describe the uprisings in Tunisia. On January 4, 2011, Christian Science Monitor asked whether the Middle East was experiencing an “Arab Spring?, Or Arab winter?”. Again on January 6, 2011, Marc Lynch of Foreign Policy inquired, “Are we seeing the beginnings of the Obama administration equivalent of the 2005 “Arab Spring.” A US commentator first used “Arab Spring” after a short-lived Middle Eastern democracy movement in 2005. The term is also connected to George W. Bush, who referenced the phrase to refer to Arab leaders who were opening political spaces for citizen activism in 2005 [18].
