How structure shapes dynamics: Knowledge development in Wikipedia - A network multilevel modeling approach.
Author(s) / Creator(s)
Halatchliyski, I.
Cress, U.
Other kind(s) of contributor
Leibniz-Institut für Wissensmedien
Abstract / Description
Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base.
Persistent Identifier
Date of first publication
2014
Journal title
PLoS ONE
Volume
9
Page numbers
e111958
Publication status
publishedVersion
Review status
peerReviewed
Is version of
10.1371/journal.pone.0111958
Citation
-
journal.pone.0111958.PDFAdobe PDF - 351.63KBMD5: 60238293451f35d2cae2144ba43a9c34
-
There are no other versions of this object.
-
Author(s) / Creator(s)Halatchliyski, I.
-
Author(s) / Creator(s)Cress, U.
-
Other kind(s) of contributorLeibniz-Institut für Wissensmedien
-
PsychArchives acquisition timestamp2017-08-28T11:11:06Z
-
Made available on2017-08-28T11:11:06Z
-
Date of first publication2014
-
Abstract / DescriptionUsing a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base.
-
Publication statuspublishedVersion
-
Review statuspeerReviewed
-
Persistent Identifierhttps://hdl.handle.net/20.500.12034/487
-
Persistent Identifierhttps://doi.org/10.23668/psycharchives.695
-
Is version of10.1371/journal.pone.0111958
-
TitleHow structure shapes dynamics: Knowledge development in Wikipedia - A network multilevel modeling approach.
-
DRO typearticle
-
Leibniz institute name(s) / abbreviation(s)IWM
-
Leibniz subject classificationPsychologie
-
Journal titlePLoS ONE
-
Page numberse111958
-
Volume9
-
Visible tag(s)Version of Record