A clustering approach to infer Wikipedia contributors' profile

Abstract : Recent studies have improved our knowledge about the different types or prooles of online contributors, from casual to very involved ones, through focused people. But they use very complex methodologies, making their replication by the practitioners limited. We show on both Romanian and Danish wikis that using only the edit and their distribution over time to feed clustering techniques, allows to build these prooles with good accuracy and stability. is suggests that light monitoring of newcomers may be suucient to adapt the interaction with them and to increase the retention rate. CCS CONCEPTS • Human-centered computing → Empirical studies in collaborative and social computing;
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01832902
Contributeur : Nicolas Jullien <>
Soumis le : lundi 9 juillet 2018 - 10:47:19
Dernière modification le : jeudi 7 février 2019 - 16:47:52

Fichier

clustering-approach-infer_open...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité - Pas de modifications 4.0 International License

Identifiants

Citation

Shubham Krishna, Romain Billot, Nicolas Jullien. A clustering approach to infer Wikipedia contributors' profile. ACM. OPENSYM'18, Aug 2018, Paris, France. OPENSYM'18, 2018, 〈Http://www.opensym.org〉. 〈10.1145/3233391.3233968〉. 〈hal-01832902〉

Partager

Métriques

Consultations de la notice

77

Téléchargements de fichiers

43