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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*
SOCIUM—Research Center on Inequality and Social Policy, University of Bremen, Bremen, Germany
Tom Töpfer
SOCIUM—Research Center on Inequality and Social Policy, University of Bremen, Bremen, Germany Institute for Educational Science, University of Hildesheim, Hildesheim, Germany (email:
Jürgen Pfeffer
Bavarian School of Public Policy, Technical University of Munich, Munich, Germany (email:
*Corresponding author. Email:
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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.

Research Article
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© The Author(s) 2020. Published by Cambridge University Press


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


Antonucci, T. C. (1986). Hierarchical mapping technique. Generations: Journal of the American Society on Aging, 10(4), 1012.Google Scholar
Antonucci, T., Akiyama, H., & Takahashi, K. (2004). Attachment and close relationships across the life span. Attachment & Human Development, 6(4), 353370.CrossRefGoogle ScholarPubMed
Bailey, S., & Marsden, P. V. (1999). Interpretation and interview context: Examining the General Social Survey name generator using cognitive methods. Social Networks, 21, 287309.CrossRefGoogle Scholar
Bearman, P., & Parigi, P. (2004). Cloning headless frogs and other important matters: Conversation topics and network structure. Social Forces, 83(4), 535557.Google Scholar
Bell, D. C., Belli-McQueen, B., & Haider, A. (2007). Partner naming and forgetting: Recall of network members. Social Networks, 29(2), 279299.CrossRefGoogle ScholarPubMed
Bellotti, E. (2016). Qualitative methods and visualizations in the study of friendship networks. Sociological Research Online, 21(2), 119.CrossRefGoogle Scholar
Bernard, H. R., Killworth, P., & Sailer, L. (1981). Summary of research on informant accuracy in network data and the reverse small world problem. Connections, 4(2), 1125.Google Scholar
Bernardi, L., Keim, S., & Klärner, A. (2014). Social networks, social influence, and fertility in Germany: A mixed-method research design. In Dominguez, S., & Hollstein, B. (Eds.), Mixed methods social networks research (pp. 121152). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Bernardi, L., Keim, S., & von der Lippe, H. (2007). Social influence on fertility. A comparative mixed methods study in eastern and western Germany. Journal of Mixed Methods Research, 1(1), 2347.Google Scholar
Bilecen, B. (2016). A personal network approach in mixed-methods design to investigate trans-national social protection. International Review of Social Research, 6(4), 233244.CrossRefGoogle Scholar
Brashears, M. E., & Quintane, E. (2015). The microstructures of network recall: How social networks are encoded and represented in human memory. Social Networks, 41, 113126.Google Scholar
Brewer, D. D. (1995). The social structural basis of the organization of persons in memory. Human Nature, 6(4), 379403.CrossRefGoogle ScholarPubMed
Brewer, D. D. (2000). Forgetting in the recall-based elicitation of personal and social networks. Social Networks, 22(1), 2943.CrossRefGoogle Scholar
Brewer, D. D., Rinaldi, G., Mogoutov, A., & Valente, T. W. (2005). A quantitative review of associative patterns in the recall of persons. Journal of Social Structure, 6(1). Retrieved from Scholar
Carrasco, J. A., Hogan, B., Wellman, B., & Miller, E. J. (2008). Collecting social network data to study social activity-travel behavior: An egocentric approach. Environment and Planning B: Planning and Design, 35(6), 961980.CrossRefGoogle Scholar
Coates, D. L. (1985). Adolescent Social record, your social map, social network record. In Johanes, R. L. (Eds.), Handbook of tests and measurements for black populations (pp. 269285). Hampton: Cobb & Henry Publishers.Google Scholar
Coromina, L., & Coenders, G. (2006). Reliability and validity of egocentered network data collected via web: A meta-analysis of multilevel multitrait multimethod studies. Social Networks, 28(3), 209231.CrossRefGoogle Scholar
Dobbie, F., Reith, G., & McConville, S. (2018). Utilising social network research in the qualitative exploration of gamblers’ social relationships. Qualitative Research, 18(2), 207223.CrossRefGoogle Scholar
Eddens, K., & Fagan, J. M. (2018). Comparing nascent approaches for gathering alter-tie data for egocentric studies. Social Networks, 55, 130141.Google Scholar
Ericsson, K. A., & Simon, H. A. (1993). Protocol analysis: Verbal reports as data. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Fagan, J. M. & Eddens, K. S. (2015). OpenEddi: A Network Data Collection Tool. Version 0.3, Lexington, KY: Flaming Fox, LLC.Google Scholar
Feld, S. L. (1981). The focused organization of social ties. American Journal of Sociology, 86(5), 10151035.CrossRefGoogle Scholar
Gamper, M., Schönhuth, M., & Kronenwett, M. (2012). Bringing qualitative and quantitative data together: Collecting network data with the help of software tool VennMaker. In Safar, M., & Mahdi, K. (Eds.), Social networking and community behavior modeling: Qualitative and quantitative measures (pp. 193213). Hershey: IGI Global.Google Scholar
Haselmair, R., Pirker, H., Kuhn, E., & Vogl, C. R. (2014). Personal networks: A tool for gaining insight into the transmission of knowledge about food and medicinal plants among Tyrolean (Austrian) migrants in Australia, Brazil and Peru. Journal of Ethnobiology and Ethnomedicine, 10(1). doi:10.1186/1746-4269-10-1.Google ScholarPubMed
Häussling, R. (2014). A network analytical four-level concept for an interpretation of social interaction in terms of structure and agency. In Dominguez, S., & Hollstein, B. (Eds.), Mixed methods social networks research: Design and applications (pp. 121177). New York: Cambridge University Press.Google Scholar
Hennig, M., Brandes, U., Pfeffer, J., & Mergel, I. (2012). Studying social networks: A guide to empirical research. Frankfurt & New York: Campus Verlag.Google Scholar
Hepp, A., Roitsch, C., & Berg, M. (2016). Investigating communication networks contextually: Qualitative network analysis as cross-media research. Mediekultur: Journal of Media and Communication Research, 32(60), 87106.CrossRefGoogle Scholar
Hersberger, J. (2003). A qualitative approach to examining information transfer via social networks among homeless populations. The New Review of Information Behaviour Research, 4(1), 95108.Google Scholar
Herz, A., & Petermann, S. (2017). Beyond interviewer effects in the standardized measurement of egocentric networks. Social Networks, 50, 7082.Google Scholar
Herz, A., Peters, L., & Truschkat, I. (2015). How to do qualitative structural analysis: The qualitative interpretation of network maps and narrative interviews. Forum Qualitative Sozialforschung/Forum Qualitative Social Research, 16(1), Art. 9. Retrieved from Scholar
Hogan, B., Carrasco, J. A., & Wellman, B. (2007). Visualizing personal networks: Working with participant-aided sociograms. Field Methods, 19(2), 116144.Google Scholar
Hogan, B., Melville, J. R., Phillips, G. L. II, Janulis, P., Contractor, N., Mustanski, B. S., & Birkett, M. (2016). Evaluating the paper-to-screen translation of participant-aided sociograms with high-risk participants. In Proceedings of the 2016 CHI conference on human factors in computing systems – CHI’16 (pp. 53605371).CrossRefGoogle Scholar
Hollstein, B. (2002). Soziale Netzwerke nach der Verwitwung. Wiesbaden: VS Verlag.CrossRefGoogle Scholar
Hollstein, B. (2011). Qualitative Approaches. In Scott, J., & Carrington, P. J. (Eds.), The SAGE handbook of social network analysis (pp. 404417). London/New Dehli: SAGE.Google Scholar
Hollstein, B., Behrmann, L., & Pfeffer, J. (2013). Touchscreen-gesteuerte Instrumente zur Erhebung egozentrierter Netzwerke. In Schönhuth, M., Gamper, M., Kronenwett, M., & Stark, M. (Eds.) Visuelle Netzwerkforschung: Qualitative, quantitative und partizipative Zugänge (pp. 121136). Bielefeld: Transcript.Google Scholar
Hollstein, B., & Pfeffer, J. (2010). Netzwerkkarten als Instrument zur Erhebung egozentrierter Netzwerke. In Soeffner, H.-G. (Ed.), Unsichere Zeiten. Verhandlungen des 34. Kongress der Deutschen Gesellschaft für Soziologie, 6.-10. Oktober 2008, Jena (pp. 113). Frankfurt am Main: Campus.Google Scholar
Kahn, R. L., & Antonucci, T. C. (1980). Convoys over the life course: Attachment, roles, and social support. In Baltes, P. B., & Orville, G. B. (Eds.), Life-span development and behavior (pp. 253286). New York: Academic Press.Google Scholar
Keupp, H., Ahbe, T., Gmür, W., Höfer, R., Mitzscherlich, B., Kraus, W., & Straus, F. (1997). Identitätskonstruktionen. Das Patchwork der Identitäten in der Spätmoderne. Reinbek: Rowohlt.Google Scholar
Kuhns, L. M., Birkett, M., Mustanski, B., Muth, S. Q., Latkin, C., Ortiz-Estes, I., & Garofalo, R. (2015). Methods for collection of participant-aided sociograms for the study of social, sexual and substance-using networks among young men who have sex with men. Connections, 35(1) doi:10.1186/1746-4269-10-1.CrossRefGoogle Scholar
Lang, F. L., & Carstensen, L. L. (1994). Close emotional relationships in late life: Further support for proactive aging in the social domain. Psychology and Aging, 9(2), 315324.CrossRefGoogle ScholarPubMed
Levin, D. Z., Walter, J., & Murnighan, J. K. (2011). Dormant ties: The value of reconnecting. Organization Science, 22(4), 923939.Google Scholar
Marsden, P. V. (2011). Survey methods for network data. In Scott, J. S., & Carrington, P. J. (Eds.), The sage handbook of social network analysis (pp. 370386). Thousand Oaks, CA: Sage.Google Scholar
Marsden, P. V., & Campbell, K. E. (1984). Measuring tie strength. Social forces, 63(2), 482501.CrossRefGoogle Scholar
McCarty, C., Molina, J. L., Aguilar, C., & Rota, L. (2007). A comparison of social network mapping and personal network visualization. Field Methods, 19(2), 145162.CrossRefGoogle Scholar
McPherson, M., Smith-Lovin, L., & Brashears, M. E. (2006). Social isolation in America: Changes in core discussion networks over two decades. American Sociological Review, 71(3), 353375.CrossRefGoogle Scholar
Molina, J. L., Maya-Jariego, I., & McCarty, C. (2014). Giving meaning to social networks: Methodology for conducting and analyzing interviews based on personal network visualizations. In Domínguez, S., & Hollstein, B. (Eds.), Mixed methods social networks research: Design and applications (pp. 305335). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Pahl, R., & Spencer, L. (2004). Capturing personal communities. In Phillipson, C., Allan, G., & Morgan, D. (Eds.), Social networks and social exclusion (pp. 7296). Aldershot: Ashgate.Google Scholar
Perry, B., Pescosolido, B., & Borgatti, S. (2018). Egocentric network analysis: Foundations, methods, and models. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Pettigrew, K. E. (1997). The role of community health nurses in providing information and referral to the elderly: A study based on social network theory. London: University of Western Ontario.Google Scholar
Reyes, C. (2016). Eliciting data on social relationships: The use of hand-drawn network maps in tracing the perception of digitally mediated social ties. International Review of Social Research, 6(4), 256268.Google Scholar
Ryan, L., & D’Angelo, A. (2018). Changing times: Migrants’ social network analysis and the challenges of longitudinal research. Social Networks, 53, 148158.Google Scholar
Ryan, L., Mulholland, J., & Agoston, A. (2014). Talking ties: Reflecting on network visualisation and qualitative interviewing. Sociological Research Online, 19(2), 112.CrossRefGoogle Scholar
Samuelsson, M., Thernlund, G., & Ringström, J. (1996). Using the five field map to describe the social network of children: A methodological study. International Journal of Behavioral Development, 19(2), 327345.Google Scholar
Scheibelhofer, E. (2011). Potential of qualitative network analysis in migration studies- reflections based on an empirical analysis of young researchers’ mobility aspirations. Migration Letters, 8(2), 111120.Google Scholar
Schönhuth, M., Gamper, M., Kronenwett, M., & Stark, M. (Eds.). (2013). Visuelle Netzwerkforschung: Qualitative, quantitative und partizipative Zugänge. Bielefeld: Transcript.CrossRefGoogle Scholar
Straus, F. (1995). Egonet QF. Ein Manual zur egozentrierten Netzwerkanalyse für die qualitative Forschung. Ms.Google Scholar
Straus, F. (2002). Netzwerkanalysen. Gemeindepsychologische Perspektiven für Forschung und Praxis. Wiesbaden: Deutscher Universitätsverlag.Google Scholar
Todd, D. M. (1980). Social networks, psychosocial adaptation, and preventive/developmental interventions: The support development workshop. Paper presented at a meeting of the American Psychological Association, Montreal, Canada, September 2.Google Scholar
Tracy, M. E., & Whittaker, J. K. (1990). The social network map: Assessing social support in clinical practice. Families in Society, 71(8), 461470.Google Scholar
Tubaro, P., Ryan, L., & D’Angelo, A. (2016). The visual sociogram in qualitative and mixed-methods research. Sociological Research Online, 21(2), 118.Google Scholar
Von der Lippe, H., & Gamper, M. (2017). Drawing or tabulating ego-centered networks? A mixed-methods comparison of questionnaire vs. visualization-based data collection. International Journal of Social Research Methodology, 20(5), 425441.Google Scholar
Wagner, K. D., Syvertsen, J. L., Verdugo, S. R., Molina, J. L., & Strathdee, S. A. (2018). A mixed methods study of the social support networks of female sex workers and their primary noncommercial male partners in Tijuana, Mexico. Journal of Mixed Methods Research, 12(4), 437457.CrossRefGoogle ScholarPubMed
Wagner, M., Schütze, Y., & Lang, F. R. (1999). Social relationships in old age. In Baltes, B., & Mayer, K. U. (Eds.), The Berlin Aging Study. Aging from 70 to 100 (pp. 282301). New York: Cambridge University Press.Google Scholar
Wrzus, C., Hänel, M., Wagner, J., & Neyer, F. J. (2013). Social network changes and life events across the life span: A meta-analysis. Psychological Bulletin, 139(1), 5380.CrossRefGoogle ScholarPubMed
Zhou, W. X., Sornette, D., Hill, R. A., & Dunbar, R. I. (2005). Discrete hierarchical organization of social group sizes. Proceedings of the Royal Society B: Biological Sciences, 272(1561), 439444.Google ScholarPubMed