Journal article icon

Journal article

The structure of online social networks mirrors those in the offline world

Abstract:
We use data on frequencies of bi-directional posts to define edges (or relationships) in two Facebook datasets and a Twitter dataset and use these to create ego-centric social networks. We explore the internal structure of these networks to determine whether they have the same kind of layered structure as has been found in offline face-to-face networks (which have a distinctively scaled structure with successively inclusive layers at 5, 15, 50 and 150 alters). The two Facebook datasets are best described by a four-layer structure and the Twitter dataset by a five-layer structure. The absolute sizes of these layers and the mean frequencies of contact with alters within each layer match very closely the observed values from offline networks. In addition, all three datasets reveal the existence of an innermost network layer at ∼1.5 alters. Our analyses thus confirm the existence of the layered structure of ego-centric social networks with a very much larger sample (in total, >185,000 egos) than those previously used to describe them, as well as identifying the existence of an additional network layer whose existence was only hypothesised in offline social networks. In addition, our analyses indicate that online communities have very similar structural characteristics to offline face-to-face network
Publication status:
Published
Peer review status:
Peer reviewed

Actions

Access Document

Files:
Publisher copy:
10.1016/j.socnet.2015.04.005

Authors

More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author


More from this funder
Funder identifier:
https://ror.org/0472cxd90
Funding agency for:
Dunbar, RIM
Grant:
295663


Publisher:
Elsevier
Journal:
Social Networks More from this journal
Volume:
43
Pages:
39-47
Publication date:
2015-05-15
DOI:
EISSN:
1879-2111
ISSN:
0378-8733


Language:
English
Keywords:
Pubs id:
pubs:524828
UUID:
uuid:bea66918-1023-4e17-88d2-b66e1ce71f24
Local pid:
pubs:524828
Source identifiers:
524828
Deposit date:
2016-03-14
ARK identifier:

Terms of use


Views and Downloads

Views and downloads will return soon






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP