Understanding Open Collaboration of Wikipedia Good Articles with Factor Analysis

Huichen Chou, Donghui Lin () and Toru Ishida ()
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Huichen Chou: Department of Social Informatics, Kyoto University, Japan
Donghui Lin: Department of Social Informatics, Kyoto University, Japan
Toru Ishida: ��School of Creative Science and Engineering, Waseda University, Tokyo, Japan

Journal of Information & Knowledge Management (JIKM), 2022, vol. 21, issue 03, 1-22

Abstract: This research aims at understanding the open collaboration involved in producing Wikipedia Good Articles (GA). To achieve this goal, it is necessary to analyse who contributes to the collaborative creation of GA and how they are involved in the collaboration process. We propose an approach that first employs factor analysis to identify editing abilities and then uses these editing abilities scores to distinguish editors. Then, we generate sequence of editors participating in the work process to analyse the patterns of collaboration. Without loss of generality, we use GA of three Wikipedia categories covering two general topics and a science topic to demonstrate our approach. The result shows that we can successfully generate editor abilities and identify different types of editors. Then we observe the sequence of different editor involved in the creation process. For the three GA categories examined, we found that GA exhibited the characteristic of highly scored content-shaping ability editors involved in the later stage of the collaboration process. The result demonstrates that our approach provides a clearer understanding of how Wikipedia GA are created through open collaboration.

Keywords: Wikipedia; open collaboration; crowd intelligence; Wikipedia quality; factor analysis (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0219649222500307

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