Adaptation of fuzzy c-means method for determination the structure of social groups
DOI:
https://doi.org/10.15587/2312-8372.2015.41014Keywords:
social group structure, fuzzy clustering, linguistic variable, fuzzy c-means methodAbstract
The problem of determining the structure of social groups occurs in various scientific researches related to the necessity classification of persons on certain grounds or building a socio-demographic portrait of people of some social group. Such problems are usually solved by conducting sociological research and further statistical analysis of the results. This approach is effective, but often results in the need to attract substantial financial and human resources. So, it is important to develop the models and methods for solving this class of problems based on readily available data.
Verbal and mathematical formulation of the problem of determining the structure of a social problem of fuzzy clustering are made in the article. However, the article noted that the feature of input data is their numerical nature, making it difficult to use the classical methods of clustering objects. Also, performing clustering, in this case it is necessary to take into account the aim of problem – the nature of clusters. To solve the problem it is proposed an adapted fuzzy-c-means method, in which on the basis of expert interviews are taken into account not only the value attributes, which are characterized by objects, but also the importance of these attributes when making reference of the object to a particular cluster. Objects, in turn, are represented by means of linguistic variables on the set of which are defined the relevant metrics.
The proposed method can be effectively used for tasks related to the determination of society structure.
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