基于维基的兴趣社区:人口统计和异常值

Hiba Arnaout, Simon Razniewski, Jeff Z. Pan
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引用次数: 0

摘要

在本文中,我们发布了有关感兴趣社区的人口统计信息和异常值的数据。这些数据来自基于维基百科的来源,主要是维基数据,涵盖了7.5万个社区,例如白宫冠状病毒工作组的成员,以及34.5万个主题,例如黛博拉·比尔克斯。我们描述了用于挖掘此类数据的统计推断方法。我们以JSON格式发布以主题为中心和以组为中心的数据集,以及浏览界面。最后,我们预计该数据集可以在三个领域发挥作用:在社会科学研究中,它为人口统计分析提供了资源;在网络规模的协作式百科全书中,它作为编辑推荐器填补知识空白;在网络搜索中,它提供了关于查询主题的重要陈述列表,以提高用户参与度。该数据集可以访问:https://doi.org/10.5281/zenodo.7410436
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Wiki-Based Communities of Interest: Demographics and Outliers
In this paper, we release data about demographic information and outliers of communities of interest. Identified from Wiki-based sources, mainly Wikidata, the data covers 7.5k communities, e.g., members of the White House Coronavirus Task Force, and 345k subjects, e.g., Deborah Birx. We describe the statistical inference methodology adopted to mine such data. We release subject-centric and group-centric datasets in JSON format, as well as a browsing interface. Finally, we forsee three areas where this dataset can be useful: in social sciences research, it provides a resource for demographic analyses; in web-scale collaborative encyclopedias, it serves as an edit recommender to fill knowledge gaps; and in web search, it offers lists of salient statements about queried subjects for higher user engagement. The dataset can be accessed at: https://doi.org/10.5281/zenodo.7410436
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