Political representation bias in DBpedia and Wikidata as a challenge for downstream processing
This highlights a critical data bias problem for researchers and developers using knowledge graphs for fairness-aware content analysis, though it is incremental in addressing known issues in external data sources.
The study examined how biases in DBpedia and Wikidata affect downstream text analysis tools like Diversity Searcher, finding a staggering over-representation of the political right in the English-language DBpedia in a case study on Belgian political parties from 1990 to 2020.
Diversity Searcher is a tool originally developed to help analyse diversity in news media texts. It relies on a form of automated content analysis and thus rests on prior assumptions and depends on certain design choices related to diversity and fairness. One such design choice is the external knowledge source(s) used. In this article, we discuss implications that these sources can have on the results of content analysis. We compare two data sources that Diversity Searcher has worked with - DBpedia and Wikidata - with respect to their ontological coverage and diversity, and describe implications for the resulting analyses of text corpora. We describe a case study of the relative over- or under-representation of Belgian political parties between 1990 and 2020 in the English-language DBpedia, the Dutch-language DBpedia, and Wikidata, and highlight the many decisions needed with regard to the design of this data analysis and the assumptions behind it, as well as implications from the results. In particular, we came across a staggering over-representation of the political right in the English-language DBpedia.