Research Article: Blaunet: An R-based graphical user interface package to analyze Blau space

Date Published: October 1, 2018

Publisher: Public Library of Science

Author(s): Michael Genkin, Cheng Wang, George Berry, Matthew E. Brashears, Jacob Fisher.

http://doi.org/10.1371/journal.pone.0204990

Abstract

McPherson’s Blau space and affiliation ecology model is a powerful tool for analyzing the ecological competition among social entities, such as organizations, along a combination of sociodemographic characteristics of their members. In this paper we introduce the R-based Graphical User Interface (GUI) package Blaunet, an integrated set of tools to calculate, visualize, and analyze the statuses of individuals and social entities in Blau space, parameterized by multiple sociodemographic traits as dimensions. The package is able to calculate the Blau statuses at the nodal, dyadic, and meso levels based on three types of information: sociodemographic characteristics, group affiliations (e.g., membership in groups/organizations), and network ties. To facilitate this, Blaunet has the following five main capabilities, it can: 1) identify a list of possible salient dimensions; 2) calculate, plot, and analyze niches for social entities by measuring the social distance along the salient dimensions between individuals affiliated with them; 3) generate Blau bubbles for individuals, thereby allowing the study of interpersonal influence of similar others even with limited or no network information; 4) capture niche dynamics cross-sectionally by calculating the intensity of exploitation from the carrying capacity and the membership rate; and 5) analyze the niche movement longitudinally by estimating the predicted niche movement equations. We illustrate these capabilities of Blaunet with example datasets.

Partial Text

Blaunet is based on two fundamental concepts in sociology: Blau space and affiliation ecology. Blau space rests on the idea that human beings can be represented in a k-dimensional space, where continuous sociodemographic characteristics such as age, income, and years of education serve as the dimensions. The dimensions that structure Blau space are socially salient (i.e., they influence association probabilities) and are referred to as Blau parameters [1, 2] in honor of the eminent sociologist Peter Blau. Each person’s attributes on the Blau parameters define his or her location in the Blau space, which in turn results in the individual’s affiliation to social entities such as organizations, cultural tastes, and political preferences, while those entities are more or less competing with one another in this space.

In this section, we discuss the major capabilities of Blaunet for analyzing Blau space and use the example datasets to illustrate them. We begin by discussing a tool we developed for constructing Blau space. Researchers often have numerous sociodemographic variables at their disposal. However, not all of these are appropriate in constructing the Blau parameters. It is therefore desirable to have a principled method to identify those variables that can serve as salient dimensions for constructing a Blau space. This is the first capability of Blaunet and we discuss it in the “Salient dimension identification” subsection.

There are many features of Blaunet that are not possible to document here, but we hope that this paper, together with the S1 file supplemental manual, serves as a useful introduction to the capabilities of the package as well as the theoretical framework behind it. Of course, questions will inevitably arise that are not answered here or in the package documentation. For this reason, users can join the Blaunet Users Facebook Group at https://www.facebook.com/groups/425015561030239/ to communicate with the authors.

 

Source:

http://doi.org/10.1371/journal.pone.0204990

 

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