This paper analyzes the determinants of network structure, as measured by hierarchy and monopolization, by examining various black market networks. We examine structures of networks on the Internet Dark Net (Virtual) and compare it to network structures of traditional black markets (Ground), using agent-based modeling. The purpose of modeling these two different types of illicit markets is to understand the network structure that emerges from the interactions of the agents in each environment. Traditional black markets are relatively hierarchical, with high degree and high betweenness. We compare the density and average length of the shortest path of the simulated Ground black market networks with our simulated Virtual network. We find that hierarchy and monopolization tendencies in networks are products of different transaction costs and information asymmetries. The Internet is an effective way to lower multiple aspects of network structure. We observe that the network structure surrounding the interactions in the Virtual black market is less hierarchical and slightly more monopolistic than the network structure of the Ground market.

Our agent-based model examines the ramifications of formal defense agreements between countries. Our model builds on previous work and creates an empirically based version of a tribute model in which actors within existing real-world networks demand tribute from one another. If the threatened actor does not pay the tribute, the aggressing actor will engage in a decision to start a war. Tribute and war payments are based on a measure of the country's wealth. We utilize the Correlates of War dataset to provide us with worldwide historical defense alliance information. Using these networks as our initial conditions, we run the model forward from four prominent historical years and simulate the interactions that take place as well as the changes in overall wealth. Agents in the model employ a cost benefit analysis in their decision of whether or not to go to war. This model provides results that are in qualitative agreement with historical emergent macro outcomes seen over time.

PurposeThis paper tests the degree to which Sunstein's law of group polarization predicts the increase or decrease in polarization among individuals in an out-group during a polarizing event. The authors use the discourse on Parler surrounding the events of January 6th as a case study.Design/methodology/approachThe study includes an overall sentiment analysis, a statistical analysis of emotions, along with eight other feelings, including anger, anticipation, disgust, fear, joy, sadness, surprise and trust. Specifically, the authors measure the differences in feelings related language used in posts as they pertain to Donald Trump and the Make America Great Again (MAGA) movement vs. Trump's Vice President Mike Pence both before and after January 6, 2021. The authors use this empirical analysis to show whether polarization in the Parler community increased or decreased after January 6th.FindingsThe authors find evidence that there is more complexity to polarization than Sunstein's theory would predict. The authors would expect a very polarized outed group to become more polarized relative to the general public after a central event; however, the authors see two extremes emerging within the Parler community (both strongly positive and strongly negative feelings toward Trump). The authors do not see unanimous consent across the Parler platform as Sunstein's theory would suggest; the out-group is becoming more polarized relative to the rest of the population. Instead, the authors observe a wide mix in reactions. The results of this study demonstrate that there is dissent even among the Parler echo chamber. For many themes surrounding the January 6th riots, Parler users express strong disagreement with each other and a lack of unity in their feelings for former President Trump.Research limitations/implicationsThe results suggest further research into polarization of outed groups and the policy implications of their polarization changes over time.Practical implicationsIncreases in group polarization are often a motivator for public policy and are further becoming a major focus for research. Brookings' authors Stephanie Forrest and Joshua Daymude point to polarization as a substantial threat to American society, claiming “reducing extreme polarization is key to stabilizing democracy” (2022). Researchers Diana Epstein and John D. Graham demonstrate that polarized politics has impacted the “substance of rulemaking, judicial decisions, and legislation” along with “complicating long-term policy changes” (2007). The authors study how entrepreneurs have responded to this increase in polarization and its implications for public policy.Social implicationsNot only does group polarization impact all types of groups, from the social to the economic, but also it has “particular implications for insulated ‘outgroups’” (Sunstein, 1999, p. 21). Groups that are excluded by either coercion or choice from dialog with other groups become even more polarized and extreme (Sunstein, 1999; Turner et al., 1989).Originality/valueThe authors have engaged in an empirical analysis that no other paper has addressed. This paper summarized the Parler sample data set and analyzed various themes associated with the events of January 6th, namely President Trump and MAGA themes and Vice President Pence. The analysis demonstrated a dramatic increase in negative sentiment and emotion related to Vice President Mike Pence after January 6th as well as mixed support for President Trump and an increase in disgust before and after the Capitol riot.