Identifying Frostquakes in Central Canada and Neighbouring Regions in the United States with Social Media
|Identifying Frostquakes in Central Canada and Neighbouring Regions in the United States with Social Media|
|Author(s)||Anderw C.W. Leung, William A. Gough, Yehong Shi|
|Editor(s)||Michael Leitner, Jamal Jokar Arsanjani|
|Published in||Citizen Empowered Mapping|
|Keyword(s)||Frostquake, Cryoseism, Social media, Crowdsourcing, Collaborative mapping|
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Identifying Frostquakes in Central Canada and Neighbouring Regions in the United States with Social Media is a 2017 book chapter written in English by Anderw C.W. Leung, William A. Gough, Yehong Shi and published in Citizen Empowered Mapping.
Following the ice storm of December 2013 in southern Ontario, the general public heard noises that resembled falling trees and reported these occurrences on social media. These were identified as a rare phenomenon called cryoseism, or more commonly known as frostquakes. These occurrences became the first large-scale documented frostquakes in Canada. Using meteorological metrics, we were able to forecast two subsequent frostquake events in January 2014 that coincided with reports on social media. In total, six more episodes of frostquakes as well as their locations were identified in January and February of 2014. Results showed that in central Canada, frostquake occurrences ranged from Windsor, Ontario to the west to Montreal, Quebec to the east and from Niagara Falls, Ontario to the south to North Bay, Ontario to the north. In the United States, the reports came from states bordering the Great Lakes and the New England areas. Two frostquake clusters were identified, one in and around the Greater Toronto Area and the other in eastern Wisconsin. Frostquakes were most frequently heard at nighttime. We critically assess the use of social media as an observation network including the possibility of false positives and population bias. This study demonstrates that rare phenomena such as frostquakes can be identified and assessed using data gathered through social media.
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- "Heilman JM, West AG (2015) Wikipedia and medicine: quantifying readership, editors, and the significance of natural language. J Med Internet Res 17(3)e62. doi:10.2196/jmir.4069" (create it!)
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