Wiki-based Communities of Interest: Demographics and Outliers

• URL: http://arxiv.org/abs/2303.09189v2
• Date: Fri, 17 Mar 2023 08:34:30 GMT
• Title: Wiki-based Communities of Interest: Demographics and Outliers
• Authors: Hiba Arnaout, Simon Razniewski, Jeff Z. Pan
• Abstract summary: Identified from Wiki-based sources, the data covers 7.5k communities, such as members of the White House Coronavirus Task Force. We release subject-centric and group-centric datasets in format, as well as a browsing interface.
• Score: 18.953455338226103
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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, such as 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 this research can have an impact on: 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.

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