Social Network Analysis of Participatory Management and Social Capital among Livestock Beneficiaries in Yazd Province

Authors

1 Assistant Professor of Rangeland Management Department, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor , Iran

2 Assistant Professor, Department Anthropology, University of Sistan & Baluchestan, Iran.

3 Assistant Professor in Institute for Cultural and Social Studies. Tehran, Iran.

Abstract

The present study has measured the part of the cognitive social capital relating to values such as participation and social cohesion. The method of this study is based on the network analysis and this network is included all local livestock beneficiaries in Yazd Province. Quantitative and qualitative information necessary for the study were collected through interviews and questionnaires of network analysis. Then through software of network analysis including UCINET and Netdraw, the relationships were analyzed using mathematical indices of density, size, link reciprocity and centralization and also the concepts of structural holes and cut points. Results indicate poor networks of participation in intergroup relationships of local beneficiaries having island social structure with fragile relationships influenced by multiple structural holes. Evaluation shows that the density index in network of participation was weak, indicating poor social cohesion and reduced resilience of livestock beneficiaries when facing with environmental stresses. The analysis of the index of link reciprocity indicates poor mutual cooperation and low stability of network. Analysis of motioned indices show that the relations structure of this community suffers from a social disorder. High centralization of central actors in internal links rather than external links is a factor preventing the formation of intermediate relationships at the macro level. Absence of these people with appropriate distribution has reduced creativity, social cohesion necessary in dealing with environmental problems especially drought.

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