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Communication Dans Un Congrès Année : 2016

Mining team characteristics to predict Wikipedia article quality

Résumé

In this study, we were interested in studying which characteristics of virtual teams are good predictors for the quality of their production. The experiment involved obtaining the Spanish Wikipedia database dump and applying different data mining techniques suitable for large data sets to label the whole set of articles according to their quality (comparing them with the Featured/Good Articles, or FA/GA). Then we created the attributes that describe the characteristics of the team who produced the articles and using decision tree methods, we obtained the most relevant characteristics of the teams that produced FA/GA. The team's maximum efficiency and the total length of contribution are the most important predictors. This article contributes to the literature on virtual team organization.
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Dates et versions

hal-01354368 , version 1 (18-08-2016)

Identifiants

  • HAL Id : hal-01354368 , version 1

Citer

Grace Gimon Betancourt, Armando Segnini, Carlos Trabuco, Amira Rezgui, Nicolas Jullien. Mining team characteristics to predict Wikipedia article quality. OpenSym 2016 : 12th International Symposium on Open Collaboration, Aug 2016, Berlin, Germany. pp.1 - 9. ⟨hal-01354368⟩
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