Complex Network Analysis of Mass Violation, Specifically Mass Killing.

Area of Science:

• Social Sciences
• Political Science
• Data Science

Background:

• News media reports on societal social and political conditions.
• Publicly available digital event datasets enable the study of complex networks, including mass violations like Mass Killings.
• Previous research has explored various approaches to understand these events and the actors involved.

Purpose of the Study:

• To identify and formulate conflicts from an actor's perspective on a global scale over a defined period.
• To generalize this conflict analysis process for application to news at any level, not exclusively global.

Main Methods:

• Utilizing publicly available digital event datasets.
• Analyzing network structures, including actor mentions, co-actor mentions, and actor degrees.
• Observing power law distribution in network metrics to identify dominant actor behavior.

Main Results:

• Power law distributions indicate dominant behavior of influential actors whose networks grow over time.
• The United States, France, and Israel identified as major players in propagating Mass Killings over the last 20 years.
• Evidence suggests that removing influential actors can disrupt the spread of conflicts.

Conclusions:

• Identifying and understanding influential actors in mass killings is crucial for conflict mitigation.
• The study's methodology provides a generalized framework for analyzing conflicts from an actor's perspective.
• Targeting key actors presents a potential strategy for policymakers and organizations to reduce societal conflicts.