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Analyzing Social Media Data to Enric...

Wang, Zheye.

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Analyzing Social Media Data to Enrich Human-Centric Information for Natural Disaster Management.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analyzing Social Media Data to Enrich Human-Centric Information for Natural Disaster Management./
Author:	Wang, Zheye.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	120 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-07, Section: A.
Contained By:	Dissertations Abstracts International80-07A.
Subject:	Geography. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13819479
ISBN:	9780438773059

Analyzing Social Media Data to Enrich Human-Centric Information for Natural Disaster Management.
Wang, Zheye.

Analyzing Social Media Data to Enrich Human-Centric Information for Natural Disaster Management. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 120 p.

Source: Dissertations Abstracts International, Volume: 80-07, Section: A.

Thesis (Ph.D.)--Kent State University, 2018.

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

Over the past several decades, the frequency and intensity of natural disasters have dramatically increased, causing great damage to human society. To reduce the impact of disasters to humanity, social media data are increasingly used to provide useful human-centric information for better accomplishing various management tasks during all disaster phases, i.e. mitigation, preparedness, response, and recovery. Four dimensions including space, time, content, and network in social media data have received particular attention in literature. A framework has been developed in this dissertation to systematically evaluate the four dimensions in social media data and address the following questions: (1) which combinations of dimensions have been implemented more (or less) frequently in existing studies? (2) what research questions and data analysis tasks could be raised based on the combinations of these dimensions? (3) how to improve the synthesis of social media data with remote sensing imagery and census data? This dissertation has two case studies. The first one shows how to separately analyze the four dimensions with kernel density estimation, histograms, latent Dirichlet allocation (LDA), and social network analysis to gain insights into situational awareness in wildfire hazards. The second case study develops a novel approach to integrate space, time, and content dimensions and enable a space-time analysis of social responses to Hurricane Sandy. This dissertation improves the understanding of the role of social media in natural disaster management.

ISBN: 9780438773059Subjects--Topical Terms:

524010
Geography.
Subjects--Index Terms:

Human-centric

Analyzing Social Media Data to Enrich Human-Centric Information for Natural Disaster Management.
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520 $a Over the past several decades, the frequency and intensity of natural disasters have dramatically increased, causing great damage to human society. To reduce the impact of disasters to humanity, social media data are increasingly used to provide useful human-centric information for better accomplishing various management tasks during all disaster phases, i.e. mitigation, preparedness, response, and recovery. Four dimensions including space, time, content, and network in social media data have received particular attention in literature. A framework has been developed in this dissertation to systematically evaluate the four dimensions in social media data and address the following questions: (1) which combinations of dimensions have been implemented more (or less) frequently in existing studies? (2) what research questions and data analysis tasks could be raised based on the combinations of these dimensions? (3) how to improve the synthesis of social media data with remote sensing imagery and census data? This dissertation has two case studies. The first one shows how to separately analyze the four dimensions with kernel density estimation, histograms, latent Dirichlet allocation (LDA), and social network analysis to gain insights into situational awareness in wildfire hazards. The second case study develops a novel approach to integrate space, time, and content dimensions and enable a space-time analysis of social responses to Hurricane Sandy. This dissertation improves the understanding of the role of social media in natural disaster management.
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