High level of correspondence across different news domain quality rating sets

Author:

Lin Hause123ORCID,Lasser Jana45ORCID,Lewandowsky Stephan67ORCID,Cole Rocky8,Gully Andrew8,Rand David G29ORCID,Pennycook Gordon1310ORCID

Affiliation:

1. Hill/Levene Schools of Business, University of Regina , 3737 Wascana Parkway, Regina, SK, S4S 0A2 , Canada

2. Sloan School of Management, Massachusetts Institute of Technology , 100 Main St, Cambridge, MA 02142 , USA

3. Department of Psychology, Cornell University , Uris Hall, 211, Tower Rd, Ithaca, NY 14853 , USA

4. Institute for Interactive Systems and Data Science, Graz University of Technology , Inffeldgasse 16C, 8010 Graz , Austria

5. Complexity Science Hub Vienna , Josefstädterstraße 39, 1080 Vienna , Austria

6. School of Psychological Science, University of Bristol , 12a, Priory Road, Bristol BS8 1TU , UK

7. School of Psychology, University of Western Australia , 35 Stirling Hwy, Crawley, WA 6009 , Australia

8. Jigsaw (Google LLC) , 1600 Amphitheatre Parkway, Mountain View, CA 94043 , USA

9. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology , 43 Vassar St, Cambridge, MA 02139 , USA

10. Department of Psychology, University of Regina , 3737 Wascana Parkway, Regina, SK S4S 0A2 , Canada

Abstract

Abstract One widely used approach for quantifying misinformation consumption and sharing is to evaluate the quality of the news domains that a user interacts with. However, different media organizations and fact-checkers have produced different sets of news domain quality ratings, raising questions about the reliability of these ratings. In this study, we compared six sets of expert ratings and found that they generally correlated highly with one another. We then created a comprehensive set of domain ratings for use by the research community (github.com/hauselin/domain-quality-ratings), leveraging an ensemble “wisdom of experts” approach. To do so, we performed imputation together with principal component analysis to generate a set of aggregate ratings. The resulting rating set comprises 11,520 domains—the most extensive coverage to date—and correlates well with other rating sets that have more limited coverage. Together, these results suggest that experts generally agree on the relative quality of news domains, and the aggregate ratings that we generate offer a powerful research tool for evaluating the quality of news consumed or shared and the efficacy of misinformation interventions.

Funder

Social Sciences and Humanities Research Council of Canada

Marie Sklodowska-Curie

Humboldt Foundation

Volkswagen Foundation

John Templeton Foundation

TDF Foundation

Canadian Heritage Digital Citizen Contribution Program

Google

Publisher

Oxford University Press (OUP)

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