Difference between revisions of "How Structure Shapes Dynamics: Knowledge Development in Wikipedia - a Network Multilevel Modeling Approach"
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Using a longitudinal network analysis approach, authors 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. Authors 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]], authors 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. | Using a longitudinal network analysis approach, authors 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. Authors 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]], authors 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. | ||
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| + | == Embed == | ||
| + | === Wikipedia Quality === | ||
| + | <code> | ||
| + | <nowiki> | ||
| + | Halatchliyski, Iassen; Cress, Ulrike; Cress, Ulrike. (2014). "[[How Structure Shapes Dynamics: Knowledge Development in Wikipedia - a Network Multilevel Modeling Approach]]". Public Library of Science. DOI: 10.1371/journal.pone.0111958. | ||
| + | </nowiki> | ||
| + | </code> | ||
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| + | === English Wikipedia === | ||
| + | <code> | ||
| + | <nowiki> | ||
| + | {{cite journal |last1=Halatchliyski |first1=Iassen |last2=Cress |first2=Ulrike |last3=Cress |first3=Ulrike |title=How Structure Shapes Dynamics: Knowledge Development in Wikipedia - a Network Multilevel Modeling Approach |date=2014 |doi=10.1371/journal.pone.0111958 |url=https://wikipediaquality.com/wiki/How_Structure_Shapes_Dynamics:_Knowledge_Development_in_Wikipedia_-_a_Network_Multilevel_Modeling_Approach |journal=Public Library of Science}} | ||
| + | </nowiki> | ||
| + | </code> | ||
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| + | === HTML === | ||
| + | <code> | ||
| + | <nowiki> | ||
| + | Halatchliyski, Iassen; Cress, Ulrike; Cress, Ulrike. (2014). &quot;<a href="https://wikipediaquality.com/wiki/How_Structure_Shapes_Dynamics:_Knowledge_Development_in_Wikipedia_-_a_Network_Multilevel_Modeling_Approach">How Structure Shapes Dynamics: Knowledge Development in Wikipedia - a Network Multilevel Modeling Approach</a>&quot;. Public Library of Science. DOI: 10.1371/journal.pone.0111958. | ||
| + | </nowiki> | ||
| + | </code> | ||
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| + | [[Category:Scientific works]] | ||
Latest revision as of 08:48, 8 September 2020
Authors | Iassen Halatchliyski Ulrike Cress Ulrike Cress |
|---|---|
Publication date | 2014 |
DOI | 10.1371/journal.pone.0111958 |
Links | Original |
How Structure Shapes Dynamics: Knowledge Development in Wikipedia - a Network Multilevel Modeling Approach - scientific work related to Wikipedia quality published in 2014, written by Iassen Halatchliyski, Ulrike Cress and Ulrike Cress.
Overview
Using a longitudinal network analysis approach, authors 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. Authors 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, authors 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.
Embed
Wikipedia Quality
Halatchliyski, Iassen; Cress, Ulrike; Cress, Ulrike. (2014). "[[How Structure Shapes Dynamics: Knowledge Development in Wikipedia - a Network Multilevel Modeling Approach]]". Public Library of Science. DOI: 10.1371/journal.pone.0111958.
English Wikipedia
{{cite journal |last1=Halatchliyski |first1=Iassen |last2=Cress |first2=Ulrike |last3=Cress |first3=Ulrike |title=How Structure Shapes Dynamics: Knowledge Development in Wikipedia - a Network Multilevel Modeling Approach |date=2014 |doi=10.1371/journal.pone.0111958 |url=https://wikipediaquality.com/wiki/How_Structure_Shapes_Dynamics:_Knowledge_Development_in_Wikipedia_-_a_Network_Multilevel_Modeling_Approach |journal=Public Library of Science}}
HTML
Halatchliyski, Iassen; Cress, Ulrike; Cress, Ulrike. (2014). "<a href="https://wikipediaquality.com/wiki/How_Structure_Shapes_Dynamics:_Knowledge_Development_in_Wikipedia_-_a_Network_Multilevel_Modeling_Approach">How Structure Shapes Dynamics: Knowledge Development in Wikipedia - a Network Multilevel Modeling Approach</a>". Public Library of Science. DOI: 10.1371/journal.pone.0111958.
