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Collecting egocentric network data with visual tools: A comparative study

Published online by Cambridge University Press:  26 February 2020

Betina Hollstein Open the ORCID record for Betina Hollstein [Opens in a new window] ,
Tom Töpfer  and
Jürgen Pfeffer
Betina Hollstein*
Affiliation:
SOCIUM—Research Center on Inequality and Social Policy, University of Bremen, Bremen, Germany
Tom Töpfer
Affiliation:
SOCIUM—Research Center on Inequality and Social Policy, University of Bremen, Bremen, Germany Institute for Educational Science, University of Hildesheim, Hildesheim, Germany (email: [email protected])
Jürgen Pfeffer
Affiliation:
Bavarian School of Public Policy, Technical University of Munich, Munich, Germany (email: [email protected])
*
*Corresponding author. Email: [email protected]
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Abstract

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When collecting egocentric network data, visual representations of networks can function as a cognitive aid for depicting relationships, helping to maintain an overview of the relationships, and keeping the attention of the interviewees. Additionally, network maps can serve as a narration generator in qualitative and in mixed-methods studies. While varying visual instruments are used for collecting egocentric network data, little is known about differences among visual tools concerning the influence on the resulting network data, the usability for interviewees, and data validity. The article provides an overview of existing visually oriented tools that are used to collect egocentric networks and discusses their functions, advantages, and limitations. Then, we present results of an experimental study where we compare four different visual tools with regard to networks elicited, manageability, and the impact of follow-up questions. In order to assess the manageability of the four tools, we used the thinking aloud method. The results provide evidence that the decision in favor of a specific visual tool (structured vs. unstructured) can affect the size and composition of the elicited networks. Follow-up questions greatly affect the elicited networks and follow-up cues can level out differences among tools. Respondents tend to prefer the concentric circles tool, with some differences in preferences and manageability of tools between participants with low and those with high socioeconomic status. Finally, assets and drawbacks of the four instruments are discussed with regard to data quality and crucial aspects of the data collection process when using visual tools.

Keywords

egocentric networksmixed methodsqualitative network analysisdata collectionnetwork mapsdata quality
Type
Research Article
Information
Network Science , Volume 8 , Issue 2: Special Issue Ego Networks , June 2020 , pp. 223 - 250
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s) 2020. Published by Cambridge University Press

Footnotes

Special Issue Editors: Brea L. Perry, Bernice A. Pescosolido, Mario L. Small, and Ann McCranie

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