Title |
Composition and Structure of a Large Online Social Network in the Netherlands
|
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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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 40% |
Ireland | 2 | 20% |
Netherlands | 1 | 10% |
Unknown | 3 | 30% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 60% |
Scientists | 3 | 30% |
Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
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% |