How Are Social Network Data Collected?

Craig M. Rawlings; Jeffrey A. Smith; James Moody; Daniel A. McFarland

doi:10.1017/9781139794985.005

4 - How Are Social Network Data Collected?

from Part I - Thinking Structurally

Published online by Cambridge University Press: 21 September 2023

James Moody and

Craig M. Rawlings: Affiliation:
Duke University, North Carolina
Jeffrey A. Smith: Affiliation:
Nova Scotia Health Authority
James Moody: Affiliation:
Duke University, North Carolina
Daniel A. McFarland: Affiliation:
Stanford University, California

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Summary

We outline key conceptual issues and strategies in social network data collection, focusing on the differences between realist and nominalist approaches. Given that most networks are incomplete in some way, we discuss ways to anticipate and assess problems with missing data.

Keywords

network data network surveys missing data

Type: Chapter
Information: Network Analysis
Integrating Social Network Theory, Method, and Application with R
, pp. 67 - 87

DOI: https://doi.org/10.1017/9781139794985.005 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2023

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References

Suggested Further Reading

adams, jimi. 2019. Gathering Social Network Data. Thousand Oaks, CA: Sage. (An outstanding recent overview of network data collection strategies.)Google Scholar

Bernard, H. Russell, Killworth, Peter, Kronenfeld, David, and Sailer, Lee. 1984. “The Problem of Informant Accuracy: The Validity of Retrospective Data.” Annual Review of Anthropology 13: 495–517. (This is one of a series of works that raised important questions on informant accuracy, leading to a focused research program on improving data collection quality.)Google Scholar

Birkett, Michelle, Melville, Joshua, Janulis, Patrick et al. 2021. “Network Canvas: Key Decisions in The Design of an Interviewer-Assisted Network Data Collection Software Suite.” Social Networks 66: 114–24. (A significant boon to contemporary network analysis is the ability to use graphical interface devices for data collection; Network Canvas is one such tool.)Google Scholar

Burt, Ronald. 1984. “Network Items and the General Social Survey.” Social Networks 6(4): 293–339. (This paper discusses the development of the “important matters” ego network name generator and name interpreter frameworks.)Google Scholar

Butts, Carter. 2003. “Network Inference, Error and Informant (In)accuracy: A Bayesian Approach.” Social Networks 25(2): 103–40. (An excellent formal treatment of the implications of error and missing data on network measures and methods.)CrossRef Google Scholar

Domínguez, Silvia, and Hollstein, Betina (eds.). 2014. Mixed Methods Social Networks Research: Design and Applications. New York: Cambridge University Press. (A nice combination of guide and illustration in using data sources other than traditional survey methods, including ethnographic and simulation approaches.)Google Scholar

Krackhardt, David. 1987. “Cognitive Social Structures.” Social Networks 9(2): 109–34. (Cognitive social-structural data ask each member of a setting to report on the relations amongst all others, yielding a perspective on the structure of the network from each person. While time consuming, it represents a powerful way to characterize perceptions and relations simultaneously.)CrossRef Google Scholar

Marsden, Peter V. 1990. “Network Data and Measurement.” Annual Review of Sociology 16: 435–63. (The classic work on best practices for data collection.)Google Scholar

Robins, Garry, Bright, David, Weissinger, Laurin, and Stys, Pat. 2022. “Data Collection for Social Network Research.” Social Networks 69: 1–2. (A collection of pieces on data collection best practices.)Google Scholar

Tubaro, Paola, Ryan, Louise, Casilli, Antonio A, and D’angelo, Alessio. 2021. “Social Network Analysis: New Ethical Approaches through Collective Reflexivity. Introduction to the Special Issue of Social Networks.” Social Networks 67: 1–8. (A nice collection of reflections on ethical issues in data collection.)Google Scholar