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A Statistical Approach to the Impact of Featured Articles in Wikipedia
Abstract This paper presents an empirical study on This paper presents an empirical study on the impact of featured articles on the attention that Wikipedia’s articles attract, and how this behavior differs in different editions of Wikipedia. The study is based on the analysis of the log lines registered by the Wikimedia Foundation Squid servers after having sent the appropriate content in response to the corresponding request submitted by any Wikipedia user. The analysis has been conducted regarding the six most visited editions of the Wikipedia and has involved more than 4,100 million log lines corresponding to the traffic of September, October and November 2009. The methodology of work has mainly consisted on the parsing of the requests sent by the users and on their subsequent filtering according to the study directives. Relevant information fields has been finally stored in a database for persistence and further characterization. The main results of this paper are twofold: it shows how to use the the traffic log to extract information about the use of Wikipedia, which is a novel research approach without precedences in the research community, and it analyzes whether the featured articles mechanism achieve to attract more attention or not. achieve to attract more attention or not.
Abstractsub This paper presents an empirical study on This paper presents an empirical study on the impact of featured articles on the attention that Wikipedia’s articles attract, and how this behavior differs in different editions of Wikipedia. The study is based on the analysis of the log lines registered by the Wikimedia Foundation Squid servers after having sent the appropriate content in response to the corresponding request submitted by any Wikipedia user. The analysis has been conducted regarding the six most visited editions of the Wikipedia and has involved more than 4,100 million log lines corresponding to the traffic of September, October and November 2009. The methodology of work has mainly consisted on the parsing of the requests sent by the users and on their subsequent filtering according to the study directives. Relevant information fields has been finally stored in a database for persistence and further characterization. The main results of this paper are twofold: it shows how to use the the traffic log to extract information about the use of Wikipedia, which is a novel research approach without precedences in the research community, and it analyzes whether the featured articles mechanism achieve to attract more attention or not. achieve to attract more attention or not.
Bibtextype inproceedings  +
Has author Antonio J. Reinoso + , Felipe Ortega + , Jesús M. González-Barahona + , Israel Herraiz +
Has extra keyword Featured articles +
Has keyword Wikipedia + , Usage patterns + , Traffic characterization + , Quantitative analysis +
Has reference User contribution and trust in Wikipedia + , Evaluating quality control of wikipedia's feature articles + , Learning to Trust the Crowd: Some Lessons from Wikipedia + , Creating, destroying, and restoring value in Wikipedia + , The singularity is not near: slowing growth of Wikipedia + , Is Wikipedia growing a longer tail? +
Has remote mirror https://libresoft.es/webfm_send/27  +
Language English +
Number of citations by publication 0  +
Number of references by publication 6  +
Published in KEOD +
Title A Statistical Approach to the Impact of Featured Articles in Wikipedia +
Type conference paper  +
Year 2010 +
Creation dateThis property is a special property in this wiki. 31 July 2011 16:22:41  +
Categories Publications without license parameter  + , Publications without DOI parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications  +
Modification dateThis property is a special property in this wiki. 5 June 2013 11:49:18  +
DateThis property is a special property in this wiki. 2010  +
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