Time-Varying Graphs and Social Network Analysis: Temporal Indicators and Metrics

TL;DR

This paper introduces a comprehensive approach for analyzing the evolution of social networks over time using time-varying graph formalism, capturing both short-term interactions and long-term property changes.

Contribution

It proposes a unified framework for studying dynamic social networks through sequences of static and time-varying graphs, including new indicators for temporal analysis.

Findings

New temporal indicators for social network analysis

Framework applicable to both short-term and long-term dynamics

Expresses concepts using a novel time-varying graph formalism

Abstract

Most instruments - formalisms, concepts, and metrics - for social networks analysis fail to capture their dynamics. Typical systems exhibit different scales of dynamics, ranging from the fine-grain dynamics of interactions (which recently led researchers to consider temporal versions of distance, connectivity, and related indicators), to the evolution of network properties over longer periods of time. This paper proposes a general approach to study that evolution for both atemporal and temporal indicators, based respectively on sequences of static graphs and sequences of time-varying graphs that cover successive time-windows. All the concepts and indicators, some of which are new, are expressed using a time-varying graph formalism.