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Composition and Structure of a Large Online Social Network in the Netherlands

Overview of attention for article published in PLOS ONE, April 2012
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Title
Composition and Structure of a Large Online Social Network in the Netherlands
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0034760
Pubmed ID
Authors

Rense Corten

Abstract

Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization). The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in The Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for The Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Netherlands 1 2%
Ireland 1 2%
Unknown 45 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 19%
Student > Master 5 10%
Student > Doctoral Student 5 10%
Professor 5 10%
Researcher 4 8%
Other 11 23%
Unknown 9 19%
Readers by discipline Count As %
Social Sciences 10 21%
Psychology 6 13%
Computer Science 5 10%
Medicine and Dentistry 3 6%
Economics, Econometrics and Finance 3 6%
Other 10 21%
Unknown 11 23%