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A methodological approach to the analysis of egocentric social networks in public health research: a practical example Cover

A methodological approach to the analysis of egocentric social networks in public health research: a practical example

Slovenian Journal of Public Health
Volume 55 (2016): Issue 4 (December 2016)
By: Janet Klara Djomba and  Lijana Zaletel-Kragelj  
Open Access
|Jul 2016

Figures & Tables

Figure 1

Data on the ego and alteri organized for entering social network analysis in the program E-net.
Data on the ego and alteri organized for entering social network analysis in the program E-net.

Figure 2

Data on the egocentric social network, organized in a text file for entering the transformation in the program Text2pajek.
Data on the egocentric social network, organized in a text file for entering the transformation in the program Text2pajek.

Figure 3

Data on the ego and alteri organized for entering the social network analysis.
Data on the ego and alteri organized for entering the social network analysis.

Figure 4

The ESN visualized in the program Egonet QF, showing the overall support.
The ESN visualized in the program Egonet QF, showing the overall support.

Figure 5

The egocentric social network visualized in the program Egonet QF, showing the following separate elements of the tie: a) exercise with the ego, b) support exercise, c) barrier exercise and d) support attending the workshop.
The egocentric social network visualized in the program Egonet QF, showing the following separate elements of the tie: a) exercise with the ego, b) support exercise, c) barrier exercise and d) support attending the workshop.

Figure 6

The egocentric social network visualized in the program E-net, displaying information about the alteri and alter-to-ego relationships: a) alter 1_01, b) alter 1_02, c) alter 1_03 and d) alter 1_04.
The egocentric social network visualized in the program E-net, displaying information about the alteri and alter-to-ego relationships: a) alter 1_01, b) alter 1_02, c) alter 1_03 and d) alter 1_04.

Figure 7

The egocentric social network visualized in the program Pajek.
The egocentric social network visualized in the program Pajek.

The main characteristics of the demonstrated tools for the visualization of egocentric social networks_

CharacteristicsTools
Egonet.QFE-netPajek
AvailabilityFree downloadFree downloadFree download
Preparation of input dataNo preparation of specific file formats neededDepending on the desired format, transformation into VNA file is needed.First, the creation of a text file, then the transformation into the Pajek file.
Display of different strengths of tiesDifferent strengths can be demonstrated by using circles with different distances to the ego.Strengths of ties are not shown in the network picture, but are displayed in a separate window.Different strengths of ties are shown in the network picture by different sizes of the lines between the ego and alteri.
Display of different elements of tiesDifferent elements can be demonstrated by using different sectors in the network.Elements of ties are not shown in the network picture, but are displayed in a separate window.Different elements of ties are not shown in the network picture.
Export of the figureExport as JPEG fileNo export of figuresExport as JPEG file
Calculation of numerical measuresNoHomophily and homogeneityNo
Manual freely available on-lineYesYesYes
DOI: https://doi.org/10.1515/sjph-2016-0035 | Journal eISSN: 1854-2476 | Journal ISSN: 0351-0026
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Language: English
Page range: 256 - 263
Submitted on: Apr 20, 2016
Accepted on: Jun 1, 2016
Published on: Jul 28, 2016
Published by: National Institute of Public Health, Slovenia
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
social network analysis,
qualitative research,
social environment,
social support
Related subjects:
Medicine,
Clinical medicine,
Hygiene and environmental medicine

© 2016 Janet Klara Djomba, Lijana Zaletel-Kragelj, published by National Institute of Public Health, Slovenia
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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