Attack and defense networks in a student social system

Area of Science:

• Social Network Analysis
• Graph Theory
• Sociology

Background:

• Signed networks model relationships, with negative ties crucial for understanding social phenomena like bullying.
• Negative hubs in networks are key to analyzing cyberbullying and mental health dynamics.
• Directed signed networks capture both positive (friendship) and negative (enmity) relationships.

Purpose of the Study:

• To systematically obtain and analyze directed signed networks of students in Yucatán, México.
• To introduce and compare 'attack' and 'defense' subnetworks based on negative out-degree and in-degree.
• To investigate the structural properties, community detection, and social balance of these subnetworks.

Main Methods:

• Collected and analyzed directed signed network data from nine schools (approximately 4,300 students).
• Constructed attack (high out-negative degree) and defense (high in-negative degree) subnetworks.
• Applied the Leiden algorithm for community detection and calculated social balance measures.

Main Results:

• Attack and defense subnetworks exhibit similar structural properties and significant overlap (average 60% common nodes).
• A specific range was identified where attack and defense network definitions are structurally meaningful.
• Female students' networks were generally denser across schools.

Conclusions:

• The structural similarity and overlap of attack and defense networks suggest they are not mutually exclusive.
• Findings provide insights into the conceptual relationship between network structures and bullying-related roles.
• The study offers a robust methodology for analyzing complex social dynamics in educational settings.