Political Extremism Predicts Belief in Conspiracy Theories

426 indexed citations
published 2015

Countries where authors are citing Political Extremism Predicts Belief in Conspiracy Theories

Specialization
Citations

This map shows the geographic impact of Political Extremism Predicts Belief in Conspiracy Theories. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Political Extremism Predicts Belief in Conspiracy Theories with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Political Extremism Predicts Belief in Conspiracy Theories more than expected).

Fields of papers citing Political Extremism Predicts Belief in Conspiracy Theories

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Political Extremism Predicts Belief in Conspiracy Theories. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Political Extremism Predicts Belief in Conspiracy Theories.

About Political Extremism Predicts Belief in Conspiracy Theories

This paper, published in 2015, received 426 indexed citations . Written by Jan‐Willem van Prooijen, André Krouwel and Thomas V. Pollet covering the research area of Cognitive Neuroscience, Sociology and Political Science and Artificial Intelligence. It is primarily cited by scholars working on Sociology and Political Science (386 citations), Communication (105 citations), Artificial Intelligence (98 citations), Cognitive Neuroscience (83 citations) and Health (57 citations). Published in Social Psychological and Personality Science.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1177/1948550614567356.

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