PageRank: An alarming index of probable earthquake occurrence

Abstract

Here, we introduce PageRank (PR) in a seismic network as an appropriate alarming clue before the occurrence of the event to be worthwhile in hazard probabilistic evaluation of earthquakes. Studying PR changes of two main shocks in Iran and Italy by means of temporal and spatial windows reveals that their PR values increase drastically before the event, while there is no trend for other considered locations and/or other time intervals. Therefore, the PR value seems to be an appropriate index of a place induction by previous events and its susceptibility for having a new earthquake. Moreover, summing over the PRs of areas close to the Italy event location and tracking this newly defined PR behavior show an increasing trend before the main shock implying that the close regions are influenced and become highly connected before the event as well as the earthquake location itself. It is also indicated that PR behavior is not necessarily correlated to the number of occurring earthquakes and is inherently the result of points connectivity and interactions.

The earthquake network: the best time scale for network construction

“…This metric helps to provide an overview of connectivity in the entire network: The second famous centrality in the concept of earthquake network is PageRank [12,28]. PageRank is an algorithm used to assess the ranks of nodes in a network based on their connections' levels used in the Google search engine for ranking web pages for the first time [10].…”

Comparison and Analysis of Network Construction Methods for Seismicity Based on Complex Networks

“…We will compare the network characteristics number of nodes, average degree, betweenness, coreness, and entropy of the three networks. Since these measures' values have different orders of magnitudes, the log of these measures is used to distinguish better the differences [17]. In this regard, we first obtained the log of these measures and divided them to the most considerable log value for normalization, respectively.…”

“…ey also discovered that the networks' topological characteristics change over time, corresponding to the large earthquakes [14][15][16]. Resaei et al [17] found that the PageRank value is an appropriate alarming clue before the event's occurrence, which is worthwhile in hazard probabilistic evaluation of earthquakes. However, the discovery of these laws is based on different network construction methods.…”