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Social network analysis in the context of community response to disaster / Rupak Goswami, Sanchayeeta Misra, Tandra Mondal, Rabindranath Jana.

By: Contributor(s): Material type: TextSeries: Publisher: London : SAGE Publications Ltd, 2018Description: 1 online resource : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781526444622 (ebook) :
Subject(s): DDC classification:
  • 363.348 23
Online resources: This research case outlines our experience of applying social network analysis in the context of community response to disaster in a disaster-hit community of West Bengal state in India. We describe the methodological nuances that we employed in this study to capture the nature of social networks in the community as a response to cyclone Aila. We have described the process of conducting participatory exercises with the community to identify disaster phases and how network data were collected at each stage of disaster. The analysis of data resulted in the description of social networks and the identified key actors in them at different phases of disaster. We also showed how network properties of households were associated with their resilience against disaster event. To the best of our knowledge, we are among the few researchers who have studied community-level social network in the field of disaster management and have amalgamated participatory exercises with social network analysis in similar context.
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Includes bibliographical references and index.

This research case outlines our experience of applying social network analysis in the context of community response to disaster in a disaster-hit community of West Bengal state in India. We describe the methodological nuances that we employed in this study to capture the nature of social networks in the community as a response to cyclone Aila. We have described the process of conducting participatory exercises with the community to identify disaster phases and how network data were collected at each stage of disaster. The analysis of data resulted in the description of social networks and the identified key actors in them at different phases of disaster. We also showed how network properties of households were associated with their resilience against disaster event. To the best of our knowledge, we are among the few researchers who have studied community-level social network in the field of disaster management and have amalgamated participatory exercises with social network analysis in similar context.

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