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A clustering approach to infer Wikipedia contributors' profile

Published: 22 August 2018 Publication History

Abstract

Recent studies have improved our knowledge about the different types or profiles 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 profiles with good accuracy and stability. This suggests that light monitoring of newcomers may be sufficient to adapt the interaction with them and to increase the retention rate.

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Cited By

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  • (2024)The Effect of Individual Traits on Emerging Roles in Synchronous Computer-Mediated GroupsProceedings of the ACM on Human-Computer Interaction10.1145/36410208:CSCW1(1-22)Online publication date: 26-Apr-2024
  • (2021)Users roles identification on online crowdsourced Q&A platforms and encyclopedias: a surveyJournal of Computational Social Science10.1007/s42001-021-00125-95:1(285-317)Online publication date: 8-Jun-2021

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    cover image ACM Other conferences
    OpenSym '18: Proceedings of the 14th International Symposium on Open Collaboration
    August 2018
    208 pages
    ISBN:9781450359368
    DOI:10.1145/3233391
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 August 2018

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    Author Tags

    1. Online communities
    2. Wikipedia
    3. clustering
    4. user profile

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    • M@rsouin - Région Bretagne

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    OpenSym '18

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    OpenSym '18 Paper Acceptance Rate 27 of 38 submissions, 71%;
    Overall Acceptance Rate 108 of 195 submissions, 55%

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    View all
    • (2024)The Effect of Individual Traits on Emerging Roles in Synchronous Computer-Mediated GroupsProceedings of the ACM on Human-Computer Interaction10.1145/36410208:CSCW1(1-22)Online publication date: 26-Apr-2024
    • (2021)Users roles identification on online crowdsourced Q&A platforms and encyclopedias: a surveyJournal of Computational Social Science10.1007/s42001-021-00125-95:1(285-317)Online publication date: 8-Jun-2021

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