Difference between revisions of "Quantitative Analysis and Characterization of Wikipedia Requests"
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+ | {{Infobox work | ||
+ | | title = Quantitative Analysis and Characterization of Wikipedia Requests | ||
+ | | date = 2008 | ||
+ | | authors = [[Antonio J. Reinoso]]<br />[[Jesus M. Gonzalez-Barahona]]<br />[[Felipe Ortega]]<br />[[Greogrio Robles]] | ||
+ | | doi = 10.1145/1822258.1822302 | ||
+ | | link = http://dl.acm.org/citation.cfm?id=1822302 | ||
+ | | plink = https://www.researchgate.net/profile/Antonio_Reinoso/publication/221367803_Quantitative_analysis_and_characterization_of_Wikipedia_requests/links/0c960516f358712d35000000.pdf | ||
+ | }} | ||
'''Quantitative Analysis and Characterization of Wikipedia Requests''' - scientific work related to [[Wikipedia quality]] published in 2008, written by [[Antonio J. Reinoso]], [[Jesus M. Gonzalez-Barahona]], [[Felipe Ortega]] and [[Greogrio Robles]]. | '''Quantitative Analysis and Characterization of Wikipedia Requests''' - scientific work related to [[Wikipedia quality]] published in 2008, written by [[Antonio J. Reinoso]], [[Jesus M. Gonzalez-Barahona]], [[Felipe Ortega]] and [[Greogrio Robles]]. | ||
== Overview == | == Overview == | ||
Authors poster describes the quantitative analysis carried out to study the use of the [[Wikipedia]] system by its users with special focus on the identification of time and kind-of-use patterns, characterization of traffic and workload, and comparative analysis of [[different language]] editions. By filtering and classifying a large sample of the requests directed to the [[Wikimedia]] systems over 7 days authors have been able to identify important information such us the targeted namespaces, the visited resources or the requested actions. The results found include the identification of weekly and daily patterns, and several correlations between different actions on the articles. In summary, the study shows an overall picture of how the most visited language editions of the Wikipedia are being accessed by their users. | Authors poster describes the quantitative analysis carried out to study the use of the [[Wikipedia]] system by its users with special focus on the identification of time and kind-of-use patterns, characterization of traffic and workload, and comparative analysis of [[different language]] editions. By filtering and classifying a large sample of the requests directed to the [[Wikimedia]] systems over 7 days authors have been able to identify important information such us the targeted namespaces, the visited resources or the requested actions. The results found include the identification of weekly and daily patterns, and several correlations between different actions on the articles. In summary, the study shows an overall picture of how the most visited language editions of the Wikipedia are being accessed by their users. |
Revision as of 06:06, 29 January 2021
Authors | Antonio J. Reinoso Jesus M. Gonzalez-Barahona Felipe Ortega Greogrio Robles |
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Publication date | 2008 |
DOI | 10.1145/1822258.1822302 |
Links | Original Preprint |
Quantitative Analysis and Characterization of Wikipedia Requests - scientific work related to Wikipedia quality published in 2008, written by Antonio J. Reinoso, Jesus M. Gonzalez-Barahona, Felipe Ortega and Greogrio Robles.
Overview
Authors poster describes the quantitative analysis carried out to study the use of the Wikipedia system by its users with special focus on the identification of time and kind-of-use patterns, characterization of traffic and workload, and comparative analysis of different language editions. By filtering and classifying a large sample of the requests directed to the Wikimedia systems over 7 days authors have been able to identify important information such us the targeted namespaces, the visited resources or the requested actions. The results found include the identification of weekly and daily patterns, and several correlations between different actions on the articles. In summary, the study shows an overall picture of how the most visited language editions of the Wikipedia are being accessed by their users.