Drawing or tabulating ego-centered networks? A mixed-methods comparison of questionnaire vs. visualization-based data collection

Lippe, Holger von der; Gamper, Markus

doi:10.1080/13645579.2016.1227649

Cited by 16 publications

(9 citation statements)

References 46 publications

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“…The network charts are concentric circles with the respondent at the center, where she places the members of her personal network as dots with varying distance from center (indicating tie strength), and at different wedges of the circle (indicating various social groups such as peers, family and friends, etc.) (Hogan, Carrasco, & Wellman, 2007; von der Lippe & Gamper, 2017). This approach has the potential to be integrated into a semistructured interview in which the interviewer asks complementary questions about the members of personal network to contextualize the social relations and to provide examples of the relationships (Marsden, 1990).…”

Section: Partial Fusion: Qualitative and Quantitative Studies On The mentioning

confidence: 99%

Social Network Analysis: An Example of Fusion Between Quantitative and Qualitative Methods

Nooraie

Sale

Marin

et al. 2018

Journal of Mixed Methods Research

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A quantitative approach to social network analysis involves the application of mathematical and statistical techniques and graphical presentation of results. Nonetheless—as with all sciences—subjectivity is an integral aspect of network analysis, manifested in the selection of measures to describe connection patterns and actors’ positions (e.g., choosing a centrality indicator), in the visualization of social structure in graphs, and in translating numbers into words (telling the story). Here, we use network research as an example to illustrate how quantitative and qualitative approaches, techniques, and data are mixed along a continuum of fusion between quantitative and qualitative realms.

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Section: Partial Fusion: Qualitative and Quantitative Studies On The mentioning

confidence: 99%

Social Network Analysis: An Example of Fusion Between Quantitative and Qualitative Methods

Nooraie

Sale

Marin

et al. 2018

Journal of Mixed Methods Research

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“…However, we did not include treatment with just a verbal stimulus and so we cannot compare visual tools against non-visual tools (cf. Von der Lippe & Gamper, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Because the visual display can serve as a "motivational and cognitive scaffold" (Von der Lippe & Gamper, 2017: 436), it is assumed that network maps increase the proportion of revealed alters in social networks and elicit more complete networks; however, empirical verification shows mixed results (Von der Lippe & Gamper, 2017). 3 Besides, the graphical display might improve reliability (Hogan et al, 2007) and validity of network data (Coromina & Coenders, 2006;Von der Lippe & Gamper, 2017), but the evidence is scarce. In these regards, the way instruments are implemented (mode, prompts) and the role of interviewers in the application of these tools can be critical.…”

Section: Introductionmentioning

confidence: 99%

“…However, systematic research on different modes of implementation of visual tools for collecting egocentric network data is scarce (Eddens & Fagan, 2018). Additionally, most studies evaluating the use of network maps focus on specific groups, for example, gamblers (Dobbie et al, 2018), highly skilled migrants (Ryan et al, 2014), or undergraduate students (Von der Lippe & Gamper, 2017) and use one specific type of network map, for example, standardized concentric circles (Von der Lippe & Gamper, 2017), partly standardized concentric circles (Ryan et al, 2014), or structured but unstandardized concentric circles (Dobbie et al, 2018). Further questions concern the handling and manageability of visual tools; for example, Carrasco et al (2008: 968) state that the simplicity of the concentric-circle sociogram makes it ideal for collecting data "in an intuitive and easy way."…”

Section: Introductionmentioning

confidence: 99%

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Collecting egocentric network data with visual tools: A comparative study

Hollstein

Töpfer

2020

Net Sci

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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.

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“…Our approach allowed participants to thoroughly express their experiences and reflect on how their networks had changed. To help respondents focus on their networks, we constructed a physical model in the form of a network map (von der Lippe & Gamper, 2016). Participants were asked to imagine, visualise, and later describe their networks using drawing as a tool.…”

Section: Alternative Approach To Studying Network Changementioning

confidence: 99%

Examining change in entrepreneurial networks: Using visualisation as an alternative approach

Soetanto

2019

European Management Journal

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Although network-based research in entrepreneurship has considered the importance of networks for small firm growth, studies have been criticised for their contradictory inferences on how entrepreneurs should embed in networks, and for overlooking the fact that networks are dynamic in nature. In this paper, we seek to contribute to entrepreneurial network literature by exploring changes in entrepreneurial networks using a network mapping approach. To meet our research objectives, we implement an innovative research design (network mapping) where entrepreneurs visually demonstrate how their networks have changed. We find that entrepreneurial networks evolve dynamically in relation to entrepreneurial stages such as opportunity exploration, initial resource gathering, incubation, early market entry, and growth. Based on the characteristics of network, the change can be defined as the initial networks change towards support-based networks, market-based networks, and the development of core networks. Given the nature of these findings, this study contributes to fostering understanding on network changes and the effectiveness of a network mapping approach as an alternative data collection methodology in network research.

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Drawing or tabulating ego-centered networks? A mixed-methods comparison of questionnaire vs. visualization-based data collection

Cited by 16 publications

References 46 publications

Social Network Analysis: An Example of Fusion Between Quantitative and Qualitative Methods

Social Network Analysis: An Example of Fusion Between Quantitative and Qualitative Methods

Collecting egocentric network data with visual tools: A comparative study

Examining change in entrepreneurial networks: Using visualisation as an alternative approach

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