Earthquakes, Hurricanes, and Mobile Communication Patterns in the New York Metro Area: Collective Behavior during Extreme Events

TL;DR

This study analyzes wireless communication patterns during the 2011 Virginia earthquake and Hurricane Irene in New York, revealing how people’s call and text behaviors change during extreme events, with implications for emergency response.

Contribution

It introduces a novel analysis of wireless communication data to understand collective behavior during natural disasters, highlighting spatial and temporal response patterns.

Findings

Call volume anomalies are larger than text volume anomalies during earthquakes.

Response magnitude diminishes with distance from the earthquake epicenter.

Communication patterns vary spatially during hurricanes, indicating partial evacuation compliance.

Abstract

We use wireless voice-call and text-message volumes to quantify spatiotemporal communication patterns in the New York Metro area before, during, and after the Virginia earthquake and Hurricane Irene in 2011. The earthquake produces an instantaneous and pervasive increase in volume and a ~90-minute temporal disruption to both call and text volume patterns, but call volume anomalies are much larger. The magnitude of call volume anomaly diminishes with distance from earthquake epicenter, with multiple clusters of high response in Manhattan. The hurricane produces a two-day, spatially varying disruption to normal call and text volume patterns. In most coastal areas, call volumes dropped anomalously in the afternoon before the hurricane's arrival, but text volumes showed a much less consistent pattern. These spatial patterns suggest partial, but not full, compliance with evacuation orders for low-lying areas. By helping us understand how people behave in actual emergencies, wireless data patterns may assist network operators and emergency planners who want to provide the best possible services to the community. We have been careful to preserve privacy throughout this work by using only anonymous and aggregate data.