Hubs of belief networks across sociodemographic and ideological groups
Palabras clave : 
Belief system
Centrality
Graph theory
Segregation
Weighted degree
Fecha de publicación : 
2022
Editorial : 
Springer
ISSN : 
1869-5469
Nota: 
This article is licensed under a Creative Commons Attribution 4.0 International License
Cita: 
Camina, E. (Eduardo); Guell, F. (F.); Sepulcre, J. (Jorge); et al. "Hubs of belief networks across sociodemographic and ideological groups". Social Network Analysis and Mining. (12), 2022,
Resumen
Beliefs are essential components of the human mind, as they define personal identity, integration and adaptation to social groups. Most theoretical studies suggest that beliefs are organized as structured networks: the so-called belief system. According to these studies and their empirical implementation using graph-theoretical approaches, a belief is any proposition considered as true by the respondent. In a recent contribution, we introduced a novel operationalization: a proposition is a belief if (1) it is taken to be true; and (2) the subject declares to be willing to hold it even if irrefutable evidence were hypothetically argued against it. Here, we implement this operationalization using a graph theory approach to investigate the network organization of the belief system in a sample of 108 participants, as well as the differences between key ideological (left- vs. right-wingers) and sociodemographic features (younger vs. older, female vs. male). We identified a well-coordinated network of interlocked spiritual, prosocial and nature-related beliefs, which displays a dense core of 10 hub nodes. Moreover, we observed how specific social liberalist beliefs and transcendental or individualistic/prosocial viewpoints are articulated within left- and right-wingers networks or younger and older participants. Interestingly, we observed that females tend to engage in denser belief networks than male respondents. In conclusion, our research expands tangible scientific evidence of the belief system of humans through the network study of belief reports, which in turn opens innovative ways to study belief systems in social and clinical samples.

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