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Tweets as Information for Emergency Response During Weather-Related Disaster Events: Methods, Constraints and a Geographical Perspective.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Tweets as Information for Emergency Response During Weather-Related Disaster Events: Methods, Constraints and a Geographical Perspective./
Author:	Suarez Castiblanco, Angela Marcela.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	120 p.
Notes:	Source: Dissertations Abstracts International, Volume: 82-09, Section: B.
Contained By:	Dissertations Abstracts International82-09B.
Subject:	Geography. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28149173
ISBN:	9798582506256

Tweets as Information for Emergency Response During Weather-Related Disaster Events: Methods, Constraints and a Geographical Perspective.
Suarez Castiblanco, Angela Marcela.

Tweets as Information for Emergency Response During Weather-Related Disaster Events: Methods, Constraints and a Geographical Perspective. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 120 p.

Source: Dissertations Abstracts International, Volume: 82-09, Section: B.

Thesis (Ph.D.)--University of California, Santa Barbara, 2020.

This item must not be sold to any third party vendors.

The general aim of this research is to understand how social media content, generated by the general public via Twitter, can be used with volunteered geographic information and official data sources to provide information about how weather-related disaster events are experienced at a local scale. Two main objectives are addressed in this study: (1) understanding how spatio-temporal information embedded in tweets can be leveraged to summarize their content and identify local effects and damage caused by weather-related disaster events; and (2) exploring how both geographic information related to hazards and validated citizen reports can be used for assessing the reliability of tweets and to prioritize those most useful for emergency management. This research contributes to the understanding of how social media data contributed by the general public can be used to inform emergency response. Additionally, it shows that different spatial clustering methods and spatial aggregation can work both to enhance content analysis in order to summarize and identify tweets containing actionable information, and for conflating tweets with authoritative geographic data to assess tweets reliability.

ISBN: 9798582506256Subjects--Topical Terms:

524010
Geography.
Subjects--Index Terms:

Content analysis

Tweets as Information for Emergency Response During Weather-Related Disaster Events: Methods, Constraints and a Geographical Perspective.
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500 $a Source: Dissertations Abstracts International, Volume: 82-09, Section: B.
500 $a Advisor: Clarke, Keith C.
502 $a Thesis (Ph.D.)--University of California, Santa Barbara, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a The general aim of this research is to understand how social media content, generated by the general public via Twitter, can be used with volunteered geographic information and official data sources to provide information about how weather-related disaster events are experienced at a local scale. Two main objectives are addressed in this study: (1) understanding how spatio-temporal information embedded in tweets can be leveraged to summarize their content and identify local effects and damage caused by weather-related disaster events; and (2) exploring how both geographic information related to hazards and validated citizen reports can be used for assessing the reliability of tweets and to prioritize those most useful for emergency management. This research contributes to the understanding of how social media data contributed by the general public can be used to inform emergency response. Additionally, it shows that different spatial clustering methods and spatial aggregation can work both to enhance content analysis in order to summarize and identify tweets containing actionable information, and for conflating tweets with authoritative geographic data to assess tweets reliability.
590 $a School code: 0035.
650 4 $a Geography. $3 524010
650 4 $a Geographic information science. $3 3432445
653 $a Content analysis
653 $a Data quality
653 $a Emergency management
653 $a Spatial analysis
653 $a Twitter
653 $a Volunteered geographic information
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710 2 $a University of California, Santa Barbara. $b Geography. $3 1025686
773 0 $t Dissertations Abstracts International $g 82-09B.
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