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University of Illinois at Urbana-Champaign

Integrating social media and rainfall data to understand the impacts of severe weather in Argentina

Abstract

dc:description

Subtropical South America experiences some of the most intense deep convection in the world. In terms of socio-economic impacts, flooding was the most destructive natural disaster in Argentina between 1980-2010; it affected 343 million people, and caused over $222 billion USD in damages. Furthermore, the national weather service in Argentina has a history of operational issues, the most glaring of which is that a single office in Buenos Aires is responsible for forecasting for the entire country. Consequently, there is a large disconnect between the weather service and the public, which impedes effective severe weather communication. We leverage social media data to understand the public's perception and Twitter activity during heavy rainfall events. Previous studies have investigated the role of social media in circulating critical information during emergencies; however, few have looked into the impact beyond cities in the United States. Rainfall and Twitter activity demonstrate a direct relationship, yet complex, non-linear interactions are likely impacting the results. A new metric, tweeting, efficiency, is developed to account for the inherent lull in social media activity during hours people are most likely asleep. Geo-tagged posts also provide supplemental information, which is particularly advantageous for this region, as it suffers from sparse and biased data.

Degree

thesis:*
Name thesis:degree_name
M.S.
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Atmospheric Sciences
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Choi, Stella Lina
Contributors dc:contributor
  • Nesbitt, Stephen W.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • Copyright 2016 Stella Choi
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier
http://hdl.handle.net/2142/90667
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/90667

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Choi, Stella Lina. Integrating social media and rainfall data to understand the impacts of severe weather in Argentina. Thesis thesis, University of Illinois at Urbana-Champaign, 2016. http://hdl.handle.net/2142/90667