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Methodological Problems with Transformation and Size Reduction of Data Sets in Network Analysis

Methodological Problems with Transformation and Size Reduction of Data Sets in Network Analysis

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MARSCHALL, Nicolas, 2006. Methodological Problems with Transformation and Size Reduction of Data Sets in Network Analysis

@mastersthesis{Marschall2006Metho-4198, title={Methodological Problems with Transformation and Size Reduction of Data Sets in Network Analysis}, year={2006}, author={Marschall, Nicolas} }

Marschall, Nicolas 2006 Marschall, Nicolas This thesis is a methodological study in the field of social network analysis. It seeks to investigate how certain factors can interfere with the processes of data collection and data analysis, and therefore lead to invalid or unreliable results for network-analytical measures. The discussion is focused on one-mode whole-network designs with data collection by the way of questionnaires. It begins with a short introduction into the methods of network analysis and then discusses the literature on the field of the validity of network analysis in general. Afterwards the possible influencing factors investigated in this study are discussed and the analysis is described.<br /><br />In particular, nonresponse (biased and unbiased), forgetting, attempts of sampling, the omission of unimportant actors, symmetrization, dichotomization, and collapsing actors are investigated. These processes and methods are simulated by comparing the results of network-analytical measures calculated with an unchanged data set to the results of measures calculated with other variants of the same data set in which these processes have been simulated. The network-analytical measures tested are density, degree centralization, eigenvector centralization, the determination of cliques and k-plexes, degree centrality, closeness centrality, eigenvector centrality, and betweenness centrality. Density, centralization and the extent of size reduction are expected to be the main influencing factors for validity and reliability. All combinations of size reduction or transformation processes and network-analytical measures are simulated using a total of seven matrices representing different densities and centralizations. In some cases, different extents of size reduction and different strategies of dealing with the problem are investigated as well.<br /><br />The study comes to the conclusion that size reduction and transformation processes can significantly change the results of an analysis. In most cases, the error introduced into the network-analytical measures is biased in one direction, most often negative. The deviations of the estimates from the real values depend on the extent of size reduction. Density and centralization are also influencing factors in many cases; however, the direction of this influence can change. Certain network-analytical measures like closeness centrality and the determination of subgroups are especially vulnerable. Certain size-reduction and transformation processes are more dangerous than others. These results are presented in detail at the end of the thesis. eng 2011-03-24T10:13:03Z 2011-03-24T10:13:03Z deposit-license application/pdf Methodological Problems with Transformation and Size Reduction of Data Sets in Network Analysis

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