{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/90667"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/90667","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Integrating social media and rainfall data to understand the impacts of severe weather in Argentina","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Choi, Stella Lina"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Atmospheric Sciences","degree_department":null,"school":null,"contributors":["Nesbitt, Stephen W."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-07-07T19:58:12Z","date_published":"2016-07-07T19:58:12Z","updated_at":"2026-07-22T22:26:34Z","subjects":["Argentina, flooding, social media"],"languages":["en"],"rights":["Copyright 2016 Stella Choi"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/90667","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Nesbitt, Stephen W."]},{"key":"dc:creator","label":"Author","values":["Choi, Stella Lina"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-07-07T19:58:12Z","2016-04-28","2016-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Atmospheric Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Argentina, flooding, social media"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Stella Choi"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/90667"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Stella Choi, accepted the attached license on 2016-04-26 at 15:27.","The student, Stella Choi, submitted this Thesis for approval on 2016-04-27 at 12:14.","This Thesis was approved for publication on 2016-04-28 at 08:41.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9525 on 2016-07-07 at 13:33:32","Made available in DSpace on 2016-07-07T19:58:12Z (GMT). No. of bitstreams: 2 CHOI-THESIS-2016.pdf: 3132738 bytes, checksum: 244d26bc22f89f792e3e78ad69a17323 (MD5) LICENSE.txt: 4208 bytes, checksum: 9c310997fb36397ff10eefb2cf6f6116 (MD5) Previous issue date: 2016-04-28"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Integrating social media and rainfall data to understand the impacts of severe weather in Argentina"]}]}],"canonical_facts":{"dc:contributor":["Nesbitt, Stephen W."],"dc:creator":["Choi, Stella Lina"],"dc:date":["2016-07-07T19:58:12Z","2016-04-28","2016-05"],"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.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Stella Choi, accepted the attached license on 2016-04-26 at 15:27.","The student, Stella Choi, submitted this Thesis for approval on 2016-04-27 at 12:14.","This Thesis was approved for publication on 2016-04-28 at 08:41.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9525 on 2016-07-07 at 13:33:32","Made available in DSpace on 2016-07-07T19:58:12Z (GMT). No. of bitstreams: 2 CHOI-THESIS-2016.pdf: 3132738 bytes, checksum: 244d26bc22f89f792e3e78ad69a17323 (MD5) LICENSE.txt: 4208 bytes, checksum: 9c310997fb36397ff10eefb2cf6f6116 (MD5) Previous issue date: 2016-04-28"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/90667"],"dc:language":["en"],"dc:rights":["Copyright 2016 Stella Choi"],"dc:subject":["Argentina, flooding, social media"],"dc:title":["Integrating social media and rainfall data to understand the impacts of severe weather in Argentina"],"dc:type":["text"],"thesis:degree_discipline":["Atmospheric Sciences"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:34Z"}