Journal of Computational Social Science最新文献

英文中文

Bridging the offline and online: 20 years of offline meeting data of the German-language Wikipedia 架起线下和线上的桥梁:德语维基百科20年的线下会议数据

Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS

Journal of Computational Social Science

Pub Date : 2023-09-26 DOI: 10.1007/s42001-023-00225-8

Nicole Schwitter

Abstract Wikipedia is one of the most visited websites worldwide. Thousands of volunteers are contributing to it daily, making it an example of how productive non-market collaboration on a very wide scale is not only viable but also sustainable. Wikipedia’s freely available data on the online actions conducted make it a popular source of data, particularly for computer scientists and computational social scientists. This data brief will present the dewiki meetup dataset which covers the offline component of the German-language version of the online encyclopaedia Wikipedia: informal offline gatherings between Wikipedia contributors. These gatherings are organised online and information about who is attending them, where they take place and what has happened at these meetings is shared publicly. The dewiki meetup dataset covers almost 20 years of offline activity of the German-language Wikipedia, containing 4418 meetups that have been organised with information on attendees, apologies, date and place of meeting, and minutes recorded. It is a valuable source of data for social science research: it captures the development of the offline network over time of one of the largest and most sustainable online public goods and communities. The data can easily be merged with online activity data on Wikipedia which allows us to bridge the gap between offline and online behaviour.

维基百科是世界上访问量最大的网站之一。成千上万的志愿者每天都在为它做贡献，这使它成为一个例子，说明大规模的生产性非市场合作不仅可行，而且可持续。维基百科关于在线行为的免费数据使其成为一个受欢迎的数据来源，特别是对计算机科学家和计算社会科学家来说。这份数据简报将展示dewiki聚会数据集，它涵盖了在线百科全书维基百科德语版的离线部分:维基百科贡献者之间的非正式离线聚会。这些聚会是在网上组织的，有关参加会议的人、会议地点和会议上发生的事情的信息都是公开分享的。dewiki meetup数据集涵盖了德语维基百科近20年的离线活动，包含4418次组织的聚会，其中包含与会者、道歉、会议日期和地点以及会议记录的信息。它是社会科学研究的宝贵数据来源:它捕捉了最大和最可持续的在线公共产品和社区之一的离线网络随着时间的发展。这些数据可以很容易地与维基百科上的在线活动数据合并，这使我们能够弥合离线和在线行为之间的差距。

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