A Social Network Analysis on Abu Sayyaf Kidnappings

Abstract

The Abu Sayyaf Group (ASG) is a Philippine-based extremist organization globally known for engaging in terrorism, kidnappings, and various criminal activities. This study sought to comprehensively analyze Abu Sayyaf ’s kidnapping incidents using social network analysis to better understand their operational structures, patterns, and dynamics. The researchers applied centrality measurements to assess the significance of nodes in the network, along with the Girvan-Newman algorithm for community detection to identify groups sharing similar characteristics and extract groups for various purposes. The findings revealed one kidnapping node to have the highest centrality score and holding the most significant influence and numerous incoming connections within the network. Another kidnapper node in the analysis of out-degree centrality displayed a proactive role, initiating multiple connections and shaping the network’s dynamic. The community detection uncovered seven distinct communities within the network, each demonstrating unique patterns and characteristics. The findings imply that kidnappings were conducted through groups rather than individuals. The majority of networks involving ASG members participating in multiple kidnapping events hold significant implications for national security strategies.