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Abstract

Contents created by open collaboration online is an important knowledge source to the modern society nowadays. Wikipedia is a prime example which can match the quality of professional encyclopedias. Yet the percentage good quality articles are low. So how different sized teams yield similar quality work is unclear such as articles of the same Wikipedia category. By identifying different editors and studying the collaboration with the work process of Wikipedia Good Articles (GAs), one can understand how different teams create quality work in open collaboration online. To distinguish editors, this research denotes their editing activity categories and subject the editing activities to factor analysis to obtain editor characteristics in the form of quantitative scores. Then we study the collaboration by investigating editors’ engagement in the work creation process along with the article size changes. The result shows the GAs creation are largely done by editors of high scored in content-shaping characteristic. In a short period prior to GA nomination, these editors suddenly appear to work and increases the article’s size to the completed GA level. Editors without dominate editor characteristics are causing the differences in team size. This research contributes to propose a new method to understand how open collaboration creates quality work and the method can easily extend to study more Wikipedia article categories. Last, the research result implies quality work can be assured by expert to work at the end of the creation process in the open collaboration.

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Acknowledgement

This research was partially supported by a Grant-in-Aid for Scientific Research (A) (17H00759, 2017-2020) and a Grant-in-Aid for Scientific Research (B) (18H03341, 2018-2020) from the Japan Society for the Promotion of Science (JSPS).

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Correspondence to Huichen Chou .

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Chou, H., Lin, D., Ishida, T., Yamashita, N. (2020). Understanding Open Collaboration of Wikipedia Good Articles. In: Meiselwitz, G. (eds) Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing. HCII 2020. Lecture Notes in Computer Science(), vol 12195. Springer, Cham. https://doi.org/10.1007/978-3-030-49576-3_3

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  • DOI: https://doi.org/10.1007/978-3-030-49576-3_3

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