Application of Social Network Analysis (SNA) to Identify Communication Network Associated with Multi-Hazard Early Warning (MHEW) in Sri Lanka

Ishani Shehara, Chandana Siriwardana, Dilanthi Amaratunga, Richard Haigh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In Sri Lanka, there are many recurring natural hazards like floods and landslides, which often turn into crucial disasters. Therefore, there is a worldwide necessity to initiate measures to reduce disaster risk as emphasized on the Sendai Framework for Disaster Risk Reduction. In this process, Multi-Hazard Early Warnings play a vital role in which clearly defines the communication networks and enhances effective communication mechanisms. To identify the behavior of the communication network, identification of stakeholders and visualization of the network is essential. Under this study, communication networks were modelled for five frequently occurring and most critical natural hazards namely; droughts, floods, landslides, tsunami and cyclones. The stakeholder identification was done by reviewing Emergency Operation Procedures assigned for the institutions under each hazard situation. Social Network Analysis approach was used as the basis for network visualization and modelling was done using Gephi open-source software. The analyzed results were ranked based on the categories of the centrality parameter, which highlights the key stakeholders in the network. Further, the developed models were compared with the Standard Operation Procedures developed for Tsunami. The key findings of the research study can be further developed to identify and bridge the communication gap in the Multi-Hazard Early Warning Mechanism.
LanguageEnglish
Title of host publication2019 Moratuwa Engineering Research Conference (MERCon)
PublisherIEEE
Pages141-146
Number of pages6
ISBN (Electronic)9781728136325, 9781728136301
ISBN (Print) 9781728136318, 9781728136332
DOIs
Publication statusPublished - 2019
EventMoratuwa Engineering Research Conference (MERCon) 2019 - University of Moratuwa, Sri Lanka
Duration: 3 Jul 20195 Jul 2019
http://mercon.mrt.ac.lk/

Conference

ConferenceMoratuwa Engineering Research Conference (MERCon) 2019
CountrySri Lanka
Period3/07/195/07/19
Internet address

Fingerprint

communication network
network analysis
social network
disaster
stakeholder
hazard
natural hazard
tsunami
visualization
landslide
communication
cyclone
drought
software
modeling

Cite this

Shehara, Ishani ; Siriwardana, Chandana ; Amaratunga, Dilanthi ; Haigh, Richard. / Application of Social Network Analysis (SNA) to Identify Communication Network Associated with Multi-Hazard Early Warning (MHEW) in Sri Lanka. 2019 Moratuwa Engineering Research Conference (MERCon). IEEE, 2019. pp. 141-146
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title = "Application of Social Network Analysis (SNA) to Identify Communication Network Associated with Multi-Hazard Early Warning (MHEW) in Sri Lanka",
abstract = "In Sri Lanka, there are many recurring natural hazards like floods and landslides, which often turn into crucial disasters. Therefore, there is a worldwide necessity to initiate measures to reduce disaster risk as emphasized on the Sendai Framework for Disaster Risk Reduction. In this process, Multi-Hazard Early Warnings play a vital role in which clearly defines the communication networks and enhances effective communication mechanisms. To identify the behavior of the communication network, identification of stakeholders and visualization of the network is essential. Under this study, communication networks were modelled for five frequently occurring and most critical natural hazards namely; droughts, floods, landslides, tsunami and cyclones. The stakeholder identification was done by reviewing Emergency Operation Procedures assigned for the institutions under each hazard situation. Social Network Analysis approach was used as the basis for network visualization and modelling was done using Gephi open-source software. The analyzed results were ranked based on the categories of the centrality parameter, which highlights the key stakeholders in the network. Further, the developed models were compared with the Standard Operation Procedures developed for Tsunami. The key findings of the research study can be further developed to identify and bridge the communication gap in the Multi-Hazard Early Warning Mechanism.",
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Shehara, I, Siriwardana, C, Amaratunga, D & Haigh, R 2019, Application of Social Network Analysis (SNA) to Identify Communication Network Associated with Multi-Hazard Early Warning (MHEW) in Sri Lanka. in 2019 Moratuwa Engineering Research Conference (MERCon). IEEE, pp. 141-146, Moratuwa Engineering Research Conference (MERCon) 2019, Sri Lanka, 3/07/19. https://doi.org/10.1109/MERCon.2019.8818902

Application of Social Network Analysis (SNA) to Identify Communication Network Associated with Multi-Hazard Early Warning (MHEW) in Sri Lanka. / Shehara, Ishani ; Siriwardana, Chandana; Amaratunga, Dilanthi; Haigh, Richard.

2019 Moratuwa Engineering Research Conference (MERCon). IEEE, 2019. p. 141-146.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Application of Social Network Analysis (SNA) to Identify Communication Network Associated with Multi-Hazard Early Warning (MHEW) in Sri Lanka

AU - Shehara, Ishani

AU - Siriwardana, Chandana

AU - Amaratunga, Dilanthi

AU - Haigh, Richard

PY - 2019

Y1 - 2019

N2 - In Sri Lanka, there are many recurring natural hazards like floods and landslides, which often turn into crucial disasters. Therefore, there is a worldwide necessity to initiate measures to reduce disaster risk as emphasized on the Sendai Framework for Disaster Risk Reduction. In this process, Multi-Hazard Early Warnings play a vital role in which clearly defines the communication networks and enhances effective communication mechanisms. To identify the behavior of the communication network, identification of stakeholders and visualization of the network is essential. Under this study, communication networks were modelled for five frequently occurring and most critical natural hazards namely; droughts, floods, landslides, tsunami and cyclones. The stakeholder identification was done by reviewing Emergency Operation Procedures assigned for the institutions under each hazard situation. Social Network Analysis approach was used as the basis for network visualization and modelling was done using Gephi open-source software. The analyzed results were ranked based on the categories of the centrality parameter, which highlights the key stakeholders in the network. Further, the developed models were compared with the Standard Operation Procedures developed for Tsunami. The key findings of the research study can be further developed to identify and bridge the communication gap in the Multi-Hazard Early Warning Mechanism.

AB - In Sri Lanka, there are many recurring natural hazards like floods and landslides, which often turn into crucial disasters. Therefore, there is a worldwide necessity to initiate measures to reduce disaster risk as emphasized on the Sendai Framework for Disaster Risk Reduction. In this process, Multi-Hazard Early Warnings play a vital role in which clearly defines the communication networks and enhances effective communication mechanisms. To identify the behavior of the communication network, identification of stakeholders and visualization of the network is essential. Under this study, communication networks were modelled for five frequently occurring and most critical natural hazards namely; droughts, floods, landslides, tsunami and cyclones. The stakeholder identification was done by reviewing Emergency Operation Procedures assigned for the institutions under each hazard situation. Social Network Analysis approach was used as the basis for network visualization and modelling was done using Gephi open-source software. The analyzed results were ranked based on the categories of the centrality parameter, which highlights the key stakeholders in the network. Further, the developed models were compared with the Standard Operation Procedures developed for Tsunami. The key findings of the research study can be further developed to identify and bridge the communication gap in the Multi-Hazard Early Warning Mechanism.

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