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Human Communication Dynamics in Digital Footsteps: A Study of the Agreement between Self-Reported Ties and Email Networks

Overview of attention for article published in PLOS ONE, November 2011
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Title
Human Communication Dynamics in Digital Footsteps: A Study of the Agreement between Self-Reported Ties and Email Networks
Published in
PLOS ONE, November 2011
DOI 10.1371/journal.pone.0026972
Pubmed ID
Authors

Stefan Wuchty, Brian Uzzi

Abstract

Digital communication data has created opportunities to advance the knowledge of human dynamics in many areas, including national security, behavioral health, and consumerism. While digital data uniquely captures the totality of a person's communication, past research consistently shows that a subset of contacts makes up a person's "social network" of unique resource providers. To address this gap, we analyzed the correspondence between self-reported social network data and email communication data with the objective of identifying the dynamics in e-communication that correlate with a person's perception of a significant network tie. First, we examined the predictive utility of three popular methods to derive social network data from email data based on volume and reciprocity of bilateral email exchanges. Second, we observed differences in the response dynamics along self-reported ties, allowing us to introduce and test a new method that incorporates time-resolved exchange data. Using a range of robustness checks for measurement and misreporting errors in self-report and email data, we find that the methods have similar predictive utility. Although e-communication has lowered communication costs with large numbers of persons, and potentially extended our number of, and reach to contacts, our case results suggest that underlying behavioral patterns indicative of friendship or professional contacts continue to operate in a classical fashion in email interactions.

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Geographical breakdown

Country Count As %
Germany 3 3%
United States 2 2%
Portugal 1 1%
Italy 1 1%
United Kingdom 1 1%
Australia 1 1%
Japan 1 1%
Canada 1 1%
Unknown 78 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 21%
Researcher 14 16%
Student > Master 13 15%
Student > Bachelor 9 10%
Student > Doctoral Student 6 7%
Other 20 22%
Unknown 8 9%
Readers by discipline Count As %
Social Sciences 17 19%
Business, Management and Accounting 16 18%
Computer Science 16 18%
Psychology 7 8%
Economics, Econometrics and Finance 3 3%
Other 20 22%
Unknown 10 11%