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Investigating Social Media for Compl...
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Hodgkins, Frances Clara.
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Investigating Social Media for Complexity-Based Simple Rules in a Natural Disaster.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Investigating Social Media for Complexity-Based Simple Rules in a Natural Disaster./
作者:
Hodgkins, Frances Clara.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
473 p.
附註:
Source: Dissertations Abstracts International, Volume: 80-10, Section: A.
Contained By:
Dissertations Abstracts International80-10A.
標題:
Environmental Studies. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13812648
ISBN:
9781392047736
Investigating Social Media for Complexity-Based Simple Rules in a Natural Disaster.
Hodgkins, Frances Clara.
Investigating Social Media for Complexity-Based Simple Rules in a Natural Disaster.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 473 p.
Source: Dissertations Abstracts International, Volume: 80-10, Section: A.
Thesis (Ed.D.)--Grand Canyon University, 2019.
This item must not be sold to any third party vendors.
The purpose of this qualitative, descriptive study was to determine how Simple Rules emerged on the Social Media sites Twitter and YouTube in the context of the 2014 South Napa, California earthquake. The conceptual theory underpinning the study was the Eoyang CDE (containers, differences, and exchanges) model. The overarching research question was How did Simple Rules emerge on the Social Media sites Twitter and YouTube in the context of the 2014 South Napa Valley, California earthquake? The sample consisted of 138,177 microblogging Tweets from Twitter and 10 videos from YouTube. Each data set was investigated using research questions designed after the Eoyang CDE model. The study method was qualitative, and the design descriptive, since the approach was the most appropriate for creating a full description of the phenomenon. A previously collected, big, Social Media data set was used to perform qualitative data analysis. The analysis included descriptive statistics, qualitative content analysis, as well as a thematic analysis based on the conceptual model. A significant finding of this study reveals Simple Rules did emerge on Social Media resulting from multi-agent communication. Practical implications from the findings indicate leaders of disaster recovery efforts should focus Social Media efforts on the platform users, and use short statements shaped like Simple Rules to communicate messages of adaptive change and adaptive support. Finally, recommendations for further research applying complex adaptive systems theory to Social Media data sets may lead to better insights into how network-based systems self-organize in the context of disaster events.
ISBN: 9781392047736Subjects--Topical Terms:
1669635
Environmental Studies.
Investigating Social Media for Complexity-Based Simple Rules in a Natural Disaster.
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The purpose of this qualitative, descriptive study was to determine how Simple Rules emerged on the Social Media sites Twitter and YouTube in the context of the 2014 South Napa, California earthquake. The conceptual theory underpinning the study was the Eoyang CDE (containers, differences, and exchanges) model. The overarching research question was How did Simple Rules emerge on the Social Media sites Twitter and YouTube in the context of the 2014 South Napa Valley, California earthquake? The sample consisted of 138,177 microblogging Tweets from Twitter and 10 videos from YouTube. Each data set was investigated using research questions designed after the Eoyang CDE model. The study method was qualitative, and the design descriptive, since the approach was the most appropriate for creating a full description of the phenomenon. A previously collected, big, Social Media data set was used to perform qualitative data analysis. The analysis included descriptive statistics, qualitative content analysis, as well as a thematic analysis based on the conceptual model. A significant finding of this study reveals Simple Rules did emerge on Social Media resulting from multi-agent communication. Practical implications from the findings indicate leaders of disaster recovery efforts should focus Social Media efforts on the platform users, and use short statements shaped like Simple Rules to communicate messages of adaptive change and adaptive support. Finally, recommendations for further research applying complex adaptive systems theory to Social Media data sets may lead to better insights into how network-based systems self-organize in the context of disaster events.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13812648
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