Building models for social space: neighourhood-based models for social networks and affiliation structures

Mathématiques et sciences humaines. Mathematics and social sciences

Pattison, Philippa¹  Robins, Garry¹ 

关键词: social space;    dynamic;    neighbourhood;    random graph;    affiliation;   

DOI  :  10.4000/msh.2937

学科分类：数学（综合）

来源: College de France * Ecole des Hautes Etudes en Sciences Sociales (E H E S S)

【 摘 要 】

We propose a quantitative relational framework for social space. We suggest that social space cannot be specified simply in geographical, network or sociocultural terms but, rather, requires an understanding of the interdependence of relationships among different types of social entities, such as persons, groups, sociocultural resources and places. We also suggest that social space cannot be regarded as fixed: unlike the Euclidean space of Newtonian mechanics, social space is constructed, at least in part, by the social processes that it supports. In the general stochastic relational framework that we propose, relationships among social entities are regarded as the fundamental elements of social space and observed relational entities are viewed as the outcome of processes that occur in overlapping local relational neighbourhoods. Each neighbourhood corresponds to a subset of possible relational entities and is conceived as a possible site of social interaction. We show how special cases of this framework yield hierarchies of models for social networks and for affiliation structures. We also sketch some next steps in the development of this framework.

【 授权许可】

Unknown