Cover Image

A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies

The desire of people affected by crises or disasters is to return to their normal lives quickly and easily. Social media provides a platform for crisis response which helps recovery and resilience building. Therefore, this study aims to investigate how social media crisis response and information sh...

Full description

Saved in:
Bibliographic Details
Main Authors: Bukar, Umar Ali, Sidi, Fatimah, Jabar, Marzanah A., Nor, Rozi Nor Haizan, Abdullah, Salfarina, Ishak, Iskandar
Format: Article
Published: Institute of Electrical and Electronics Engineers 2022
Online Access:http://psasir.upm.edu.my/id/eprint/100191/
https://ieeexplore.ieee.org/document/9779732
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.upm.eprints.100191
record_format eprints
spelling my.upm.eprints.1001912024-07-15T03:36:26Z http://psasir.upm.edu.my/id/eprint/100191/ A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies Bukar, Umar Ali Sidi, Fatimah Jabar, Marzanah A. Nor, Rozi Nor Haizan Abdullah, Salfarina Ishak, Iskandar The desire of people affected by crises or disasters is to return to their normal lives quickly and easily. Social media provides a platform for crisis response which helps recovery and resilience building. Therefore, this study aims to investigate how social media crisis response and information shaped people’s resilience-building, either affected by the flooding or not. Data collected in Malaysia after flooding consist of 375 observations. A multi-stage analysis which consists of partial least square structural equation modeling (PLS-SEM), partial least square predictions algorithm (PLS-predict), and artificial neural networks (ANN), are employed to examine the outcome of social media crisis communications. The result shows support for the significance of crisis, crisis response, social media interaction, and information seeking and sharing are not. Furthermore, the predictive relevance of the model is strong, and the root mean square error (RMSE) obtained from ANN analysis indicated a predictive model capacity. Hence, the findings demonstrated the impact of social media crisis responses that crisis management and communication may use in decision-making. Institute of Electrical and Electronics Engineers 2022-05-23 Article PeerReviewed Bukar, Umar Ali and Sidi, Fatimah and Jabar, Marzanah A. and Nor, Rozi Nor Haizan and Abdullah, Salfarina and Ishak, Iskandar (2022) A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies. IEEE Access, 10. pp. 57266-57282. ISSN 2169-3536 https://ieeexplore.ieee.org/document/9779732 10.1109/ACCESS.2022.3176963
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description The desire of people affected by crises or disasters is to return to their normal lives quickly and easily. Social media provides a platform for crisis response which helps recovery and resilience building. Therefore, this study aims to investigate how social media crisis response and information shaped people’s resilience-building, either affected by the flooding or not. Data collected in Malaysia after flooding consist of 375 observations. A multi-stage analysis which consists of partial least square structural equation modeling (PLS-SEM), partial least square predictions algorithm (PLS-predict), and artificial neural networks (ANN), are employed to examine the outcome of social media crisis communications. The result shows support for the significance of crisis, crisis response, social media interaction, and information seeking and sharing are not. Furthermore, the predictive relevance of the model is strong, and the root mean square error (RMSE) obtained from ANN analysis indicated a predictive model capacity. Hence, the findings demonstrated the impact of social media crisis responses that crisis management and communication may use in decision-making.
format Article
author Bukar, Umar Ali
Sidi, Fatimah
Jabar, Marzanah A.
Nor, Rozi Nor Haizan
Abdullah, Salfarina
Ishak, Iskandar
spellingShingle Bukar, Umar Ali
Sidi, Fatimah
Jabar, Marzanah A.
Nor, Rozi Nor Haizan
Abdullah, Salfarina
Ishak, Iskandar
A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies
author_facet Bukar, Umar Ali
Sidi, Fatimah
Jabar, Marzanah A.
Nor, Rozi Nor Haizan
Abdullah, Salfarina
Ishak, Iskandar
author_sort Bukar, Umar Ali
title A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies
title_short A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies
title_full A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies
title_fullStr A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies
title_full_unstemmed A multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies
title_sort multistage analysis of predicting public resilience of impactful social media crisis communication in flooding emergencies
publisher Institute of Electrical and Electronics Engineers
publishDate 2022
url http://psasir.upm.edu.my/id/eprint/100191/
https://ieeexplore.ieee.org/document/9779732
_version_ 1805889894939099136
score 13.211869

Similar Items