Related papers: Surveying Wikipedians: a dataset of users and contributors' practices on Wikipedia in 8 languages

Surveying Wikipedians: a dataset of users and contributors' practices on Wikipedia in 8 languages

URL: http://arxiv.org/abs/2311.07964v2
Date: Tue, 5 Dec 2023 09:04:12 GMT
Title: Surveying Wikipedians: a dataset of users and contributors' practices on Wikipedia in 8 languages
Authors: Caterina Cruciani, L\'eo Joubert (LEST, DySoLab), Nicolas Jullien (IMT Atlantique - LUSSI, MARSOUIN, LEGO), Laurent Mell (CREAD, MARSOUIN), Sasha Piccione, Jeanne Vermeirsche (AU)
Abstract summary: dataset focuses on Wikipedia users and contains information about demographic and socioeconomic characteristics of the respondents. The data was collected using a questionnaire available online between June and July 2023.
Score: 0.0
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: The dataset focuses on Wikipedia users and contains information about demographic and socioeconomic characteristics of the respondents and their activity on Wikipedia. The data was collected using a questionnaire available online between June and July 2023. The link to the questionnaire was distributed via a banner published in 8 languages on the Wikipedia page. Filling out the questionnaire was voluntary and not incentivised in any way. The survey includes 200 questions about: what people were doing on Wikipedia before clicking the link to the questionnaire; how they use Wikipedia as readers (``professional'' and ``personal'' uses); their opinion on the quality, the thematic coverage, the importance of the encyclopaedia; the making of Wikipedia (how they think it is made, if they have ever contributed and how); their social, sport, artistic and cultural activities, both online and offline; their socio-economic characteristics including political beliefs, and trust propensities. More than 200 000 people opened the questionnaire, 100 332 started to answer, and constitute our dataset, and 10 576 finished it. Among other themes identified by future researchers, the dataset can be useful for advancing the research regarding the features of readers vs contributors of online commons, the relationship between trust, information, sources, and the use made of this information.

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