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Citation |
Misra S, Goswami R, Mondal T, Jana R. Int. J. Disaster Risk Reduct. 2017; 22: 281-296. |
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Copyright |
(Copyright © 2017, Elsevier Publishing) |
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DOI |
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PMID |
unavailable |
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Abstract |
The strength and effectiveness of social networks influence the ability of communities to cope with disaster events. Social Network Analysis (SNA) provides scope of analysing such complex networks in disaster-hit communities. We describe the application of SNA in a disaster-hit community and show the changing pattern of evolving networks during and after the disaster. The disaster event was conceptually divided into four distinct phases namely 'extreme event' (Phase-1), 'immediate community response' (Phase-2), 'relief' (Phase-3) and 'rehabilitation' (Phase-4), through a series of focus group discussions with the community. We also considered the Pre- and Post-disaster phases for before-after comparison of the community's social network. Network data for all these six phases was collected through personal interview from the affected households located besides the river embankment. For all the six phases, unique networks were found with different central nodes, although few nodes remained central in more than one the phase. Different measures of network density and mean network centrality increased from the pre-disaster stage in Phase-1, just after the disaster event, and then consistently reduced from Phase 2 to Phase 4. Then again they increased at the post-disaster phase. While the Phase-1 was characterized by endogenous nodes and ties, during the later stages, the networks assumed a core central structure constituted of both internal and external nodes, with peripheral components. The internal and external central actors maintained link between local (friends, relatives, neighbours) and external (institutional) entities. The analysis illustrates the interactions within and between community networks, and may initiate situational awareness, efficient planning, and optimal resources allocation for disaster preparedness, community resilience, and response. Language: en |
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Keywords |
Centrality; Disaster resilience; Network evolution; Social capital; Social network analysis |