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5 - How Are Social Network Data Visualized?

from Part I - Thinking Structurally

Published online by Cambridge University Press:  21 September 2023

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

Images can be powerful; and, as the saying goes, “with great power comes great responsibility.” Today, the world is suffused with images through various media, and people have come to expect pictures to tell them stories. With increased computational power, images of quantitative data are increasingly part of the “stories” one commonly sees and are powerful in communicating research findings. Many of these images are informative and effective; others are confusing, convey little actual information, or, sadly, are used to intentionally mislead for ideological reasons. Network science has always used compelling images to tell stories about structures, and the field is therefore particularly suited to make the most use of this era of data visualization. But given the vastly expanded palette of visualization available today, how does the researcher decide what is a good network image?

Type
Chapter
Information
Network Analysis
Integrating Social Network Theory, Method, and Application with R
, pp. 88 - 114
Publisher: Cambridge University Press
Print publication year: 2023

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References

Suggested Further Reading

Bender-deMoll, Skye. 2016. “ndtv: Network Dynamic Temporal Visualizations. R package version 0.10.” http://statnet.org. (Arguably the best dynamic network movie visualization tool currently available, building on work from SoNIA [Bender-deMoll & McFarland 2006]; provides a rigorous linkage between network change and screen change that minimizes display artifacts.)Google Scholar
Borner, Katy. 2010. Atlas of Science. Cambridge, MA: MIT Press. (Scientometric models of all of science; provides nice examples of visualization at scale.)Google Scholar
Casciaro, Tiziana. 1998. “Seeing Things Clearly: Social Structure, Personality and Accuracy in Social Network Perception.” Social Networks 20: 331–51. (An empirical examination of how people perceive network images.)CrossRefGoogle Scholar
Chase, Ivan D. 2006. “Music Notation: A New Method for Visualizing Social Interactions in Animals and Humans.” Frontiers in Zoology 3(1): 113. (Introduces a method for documenting micro-interactions over time using musical notation as the archetype; an elegant innovation allowing one to see the emergence of patterns over time in complex settings.)CrossRefGoogle Scholar
Freeman, Linton. 2000. “Visualizing Social Networks.” JOSS: Journal of Social Structure 1(1). (A nice overview of the history of network visualization.)Google Scholar
Lima, Manuel. 2013. Visual Complexity: Mapping Patterns of Information. Princeton, NJ: Princeton Architectural Press. (A nice book on visualizing text and meaning, including many network approaches.)Google Scholar
Lombardi, Mark. “Narrative Structures.” (A series of network-visualization artworks that explore contemporary political events. Stunning examples of art and investigation.)Google Scholar
McGrath, Cathleen, Blythe, Jim, and Krackhardt, David. 1997. “The Effect of Spatial Arrangement on Judgment and Errors in Interpreting Graphs.” Social Networks 19: 223–42. (Experimental models on how network layout affects viewers’ understanding of the underlying structure. Model paper for a problem still not settled that could use much more contemporary work.)Google Scholar
Steele, Julie, and Iliinsky, Noah. 2010. Beautiful Visualization. Sebastopol, CA: O’Reilly Media. (A survey of best practices in general data visualization.)Google Scholar
Tufte, Edward R. 2001. The Visual Display of Quantitative Information. Cheshire, CT: Graphics Press. (The classic source in the field of data visualization.)Google Scholar

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