Application of Social Network Analysis (SNA) to identify communication network associated with Multi-Hazard Early Warning (MHEW) in Sri Lanka

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