Suchergebnisse

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.

Social Network Analysis (SNA) has received growing attention among diverse academic fields for studying 'social relations' among individuals and institutions. Unfortunately, its application has remained limited in the study of livelihood systems of rural poor. Complexity in rural livelihoods has increased sharply in the face of increased pressure on natural resources and rapid shift in farm-based to non-farm based employments. This poses great challenge to successful livelihood intervention in rural areas. On one hand, rural development/extension needs to cater to diverse information and service need of the rural people; on other hand, rural institutions need to deliver livelihood-sustaining services more efficiently, which often need institutional restructuring at multiple levels. To achieve these challenges, a strong innovative analytical tool is required for understanding the complexity of rural livelihoods and the associated role of rural institutions. SNA provides excellent scope to analyse such complex systems and interactions among their components. This article proposes an outline of using SNA in livelihood system analysis. The analysis can provide answer to many questions of practical importance – Who are the influential actors in a livelihood system? Which are the key institutions contributing towards sustainable livelihoods? How do these actors interact among themselves? This will help rural development administrators to deliver livelihood-supporting services more efficiently through informed targeting and capacity building.