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  5. A Latent Space Analysis of Editor Lifecycles in Wikipedia
 
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A Latent Space Analysis of Editor Lifecycles in Wikipedia

Author(s)
Qin, Ziangju  
Greene, Derek  
Cunningham, Pádraig  
Uri
http://hdl.handle.net/10197/6611
Date Issued
2014-09-15
Date Available
2015-06-17T09:05:16Z
Abstract
Collaborations such as Wikipedia are a key part of the valueof the modern Internet. At the same time there is concern that thesecollaborations are threatened by high levels of member turnover. In thispaper we borrow ideas from topic analysis to editor activity on Wikipediaover time into a latent space that oers an insight into the evolvingpatterns of editor behavior. This latent space representation reveals anumber of dierent categories of editor (e.g. content experts, social net-workers) and we show that it does provide a signal that predicts aneditor's departure from the community. We also show that long termeditors gradually diversify their participation by shifting edit preferencefrom one or two namespaces to multiple namespaces and experience rel-atively soft evolution in their editor proles, while short term editorsgenerally distribute their contribution randomly among the namespacesand experience considerably uctuated evolution in their editor proles.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
Springer
Subjects

Machine learning

Statistics

DOI
10.1007/978-3-319-29009-6_3
Web versions
https://www.kde.cs.uni-kassel.de/ws/muse2014
Language
English
Status of Item
Peer reviewed
Journal
Revised Selected Papers from the 5th International Workshop on Big Data Analytics in the Social and Ubiquitous Context
Lecture Notes in Computer Science
Conference Details
5th International Workshop on Mining Ubiquitous and Social Environments (MUSE) at ECML, Nancy, France, 15 September 2014
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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insight_publication.pdf

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856.46 KB

Format

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Owning collection
Insight Research Collection
Mapped collections
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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