#Earthquake: Twitter as a Distributed Sensor System

TLDR

Social media feeds are emerging as geographic information sources that frequently reference events occurring at specific locations. The study analyzes the spatial and temporal characteristics of Twitter activity following a 5.8‑magnitude earthquake on the U.S. East Coast to evaluate the potential of harvested social media content for event monitoring. The authors compare Twitter feed data with crowdsourced “Did You Feel It?” reports, assessing how social media activity can be used to detect and localize earthquake impacts.

Abstract

Abstract Social media feeds are rapidly emerging as a novel avenue for the contribution and dissemination of information that is often geographic. Their content often includes references to events occurring at, or affecting specific locations. Within this article we analyze the spatial and temporal characteristics of the twitter feed activity responding to a 5.8 magnitude earthquake which occurred on the E ast C oast of the U nited S tates ( US ) on A ugust 23, 2011. We argue that these feeds represent a hybrid form of a sensor system that allows for the identification and localization of the impact area of the event. By contrasting this with comparable content collected through the dedicated crowdsourcing ‘Did You Feel It?’ ( DYFI ) website of the U . S . Geological Survey we assess the potential of the use of harvested social media content for event monitoring. The experiments support the notion that people act as sensors to give us comparable results in a timely manner, and can complement other sources of data to enhance our situational awareness and improve our understanding and response to such events.