The earthquake network: the best time scale for network construction

TL;DR

This paper investigates the optimal time scale for constructing earthquake networks by analyzing seismic data from Iran and California, demonstrating that an appropriate temporal scale enhances network features like small-worldness and centrality measures.

Contribution

It introduces a temporal network construction method and identifies the minimum time scale for optimal earthquake network analysis, improving upon previous static or large-scale approaches.

Findings

Optimal time scale improves network small-world properties

Temporal networks enhance centrality measure accuracy

Minimum data size needed for reliable earthquake network analysis

Abstract

Scientists mapped the seismic time series into networks by considering the geographical location of events as nodes and establishing links between the nodes with different rules. Applying the successive defined laws to construct the networks of seismic data, a variety of features of earthquake networks are detected (scale-free and small-world structures). Network construction models had changed in detail to optimize the performance of the verification of the minimum geographical size defined for the node. In all the studies, people try to use large data sets like years of data to ensure their results are good enough. In this work, by proposing the temporal network construction and employing the small-worldness property for data from Iran and California, we could achieve the minimum time scale needed for the best results. We verified the importance of this scale by analyzing two significant centrality measures (degree centrality and PageRank) introduced in the concept of earthquake network.