It is widely recognised that individuals with high social capital are important - in either promoting or acting as inhibitors - to the diffusion of knowledge and information. It is through ties to these individuals that others receive knowledge and hence their actions are influenced. Social network analysis (SNA) gives a methodology to achieve an understanding of how individuals are linked to those with social capital and to identify those with high social capital. In this approach, both qualitative and quantitative data can be synthesised to obtain deep understanding of the research area. However, applications of SNA are often compromised by methodological problems in relation to causality, control of exogenous effects, contamination of the sample, understanding of meaning by respondents and sampling. In this paper, with the aid of examples from Scotland, Bangladesh and Ghana the significance of these problems are illustrated and guidance given as to their resolution.
|Keywords:||Social Network Analysis, Social Capital, Development, Methodology|
Reader in Applied Statistics, School of Accounting, Economics and Statistics, Napier University, Edinburgh, Lothian, UK
Associate Professor, Department of Communitation, University of Dhaka, Dhaka, Bangladesh
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