How can the social sciences benefit from knowledge graphs? A case study on using Wikidata and Wikipedia to examine the world’s billionaires

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Daria Tisch
Franziska Pradel

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Guest Editors Wikidata 2022

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This study examines the potentials of Wikidata and Wikipedia as knowledge graphs for the social sciences. The study demonstrates how social science research may benefit from these knowledge bases by examining what we can learn from Wikidata and Wikipedia about global billionaires (2010-2022). First, knowledge graphs provide human knowledge, which can be used to generate datasets informing about, for example, political, economic, and cultural elites or other notable people. Second, knowledge graphs provide linked (open) data that can be used to examine social networks of a different kind but also enable social scientists to connect different databases to enrich their research data. We show that the English Wikipedia and, to a lesser extent, Wikidata exhibit gender and nationality biased in the coverage and information about global billionaires. Using the genealogical information that Wikidata provides, we examine the family webs of billionaires and show that at least 15% of all billionaires have a family member also being a billionaire. We discuss the challenges and limitations of using Wikidata and Wikipedia for research purposes.
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