Social patterns revealed through random matrix theory

TL;DR

This paper applies random matrix theory to weighted social networks to uncover how interaction weights influence structural properties and individual decision-making, especially during crises.

Contribution

It introduces a novel application of random matrix analysis to weighted social networks, highlighting the impact of weights on structural and behavioral patterns.

Findings

Weights significantly influence network structure.

Randomness affects individual decision-making during crises.

Weighted interactions are key to understanding societal dynamics.

Abstract

Despite the tremendous advancements in the field of network theory, very few studies have taken weights in the interactions into consideration that emerge naturally in all real world systems. Using random matrix analysis of a weighted social network, we demonstrate the profound impact of weights in interactions on emerging structural properties. The analysis reveals that randomness existing in particular time frame affects the decisions of individuals rendering them more freedom of choice in situations of financial security. While the structural organization of networks remain same throughout all datasets, random matrix theory provides insight into interaction pattern of individual of the society in situations of crisis. It has also been contemplated that individual accountability in terms of weighted interactions remains as a key to success unless segregation of tasks comes into play.