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16 - Conclusion

Network Analysis Tomorrow

from Part III - Making Structural Predictions

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

The frontiers of network analysis keep expanding with new data sources and new ways to see structure and model relations. Traces of interactions and relations are now constantly streaming and being recorded through social network platforms. New technologies are affording new ways to visualize and analyze massive online data sets, as well as flowing interactions using video and sensor data. These new data sources are being met with new data mining approaches, giving us a deeper and wider view of social structure. Moreover, these new technologies are undoubtedly changing aspects of social structure itself, as people form ties and influence one another in ways that were unimaginable a generation ago. What is missing, we contend, is a systematic way of linking these projects to a theory of social structure (as outlined in Chapter 2). We conclude by proposing three strategies for addressing open problems and moving forward in modeling social structure.

Type
Chapter
Information
Network Analysis
Integrating Social Network Theory, Method, and Application with R
, pp. 390 - 420
Publisher: Cambridge University Press
Print publication year: 2023

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