Аннотации:
© 2015 Canadian Center of Science and Education. All rights reserved. The article provides insights on the conceptualization of social mapping and its three main types: statistical, anthropological and network-oriented. Each perspective is described in detail and illustrated by examples. Artificial Neuron Networks with a particular interest to self-organizing maps are embedded in the analysis as a cutting-edge technique of social mapping now actively used by interdisciplinary researchers. The authors argue that despite the variety of social mapping techniques, they all have common features such as ordering and grouping of objects based on particular framework and empirical data, flexibility, visibility, citizens’ engagement on developing maps. Along with advantages, authors acknowledge such limitations of social mapping as data exclusion, data scale incompatibility and complexity of datasets that are beyond the cognitive abilities of the analyst.
