Description:

Have you ever noticed how your attitude can be influenced by your relationships? Traditional models of social interaction often focus on pairwise relationships, but these fall short of capturing the true complexity of our connections. This talk dives into the idea of triadic interactions, first introduced by Heider, which reveals new dimensions of the complexity of social networks. While Heider Balance Theory offers insights into how systems evolve from a random state to a balanced one by reducing tension through triadic interactions, it makes a critical assumption: all relationships are equally important. But is this really the case? Our relationships have varying levels of importance, and this issue plays a crucial role in shaping the dynamics of social systems. In this presentation, we go beyond traditional models to explore weighted triadic interactions, where the varying strengths of relationships are accounted for. This raises intriguing questions about network dynamics:

• How does a weighted, fully connected network strive to minimize unbalanced states to reduce tension?

• Does it exhibit similar behavior to unweighted systems described by Heider Balance Theory, or do unexpected dynamics emerge?

We also extend this framework to data-driven research, examining the behavior of financial networks through real-world data. Specifically, we analyze the S&P500 index (SPX) using triadic interactions to uncover the underlying network structure during periods of on and off crisis. In this presentation, we unveil the surprising interplay of weighted triads in fully connected networks, revealing unexpected patterns that can hinder social systems from achieving balance. In addition, we discover how triadic interactions shed light on the resistance of the financial network to changes.

Mahsa Bagherikalhor, Postdoctoral Scholar, Shahid Beheshti University, Tehran

Host: Istvan Kovacs