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Imputation of missing links and attributes in longitudinal social surveys
2013
Machine Learning
We propose a unified approach for imputation of the links and attributes in longitudinal social surveys which accounts for changing network topology and interdependence between the actor's links and attributes. The previous studies on the treatment of non-respondents in longitudinal social networks were mostly concerned with imputation of the missing links only or imputation effects on the networks statistics. For this study we conduct a set of experiments on synthetic and real life datasets
doi:10.1007/s10994-013-5420-1
fatcat:r37potkpjvb23eoopsltik55ry