Identifying important individual- and country-level predictors of conspiracy theorizing : A machine learning analysis

PsyCorona Study, Karen M. DOUGLAS, Robbie M. SUTTON, Caspar J. VAN LISSA, Wolfgang STROEBE, Jannis KREIENKAMP, Maximilian AGOSTINI, Jocelyn J. BÉLANGER, Ben GÜTZKOW, Georgios ABAKOUMKIN, Jamilah Hanum ABDUL KHAIYOM, Vjollca AHMEDI, Handan AKKAS, Carlos A. ALMENARA, Mohsin ATTA, Sabahat Cigdem BAGCI, Sima BASEL, Edona BERISHA KIDA, Allan B. I. BERNARDO, Nicholas R. BUTTRICKPhatthanakit CHOBTHAMKIT, Hoon‐Seok CHOI, Mioara CRISTEA, Sára CSABA, Kaja DAMNJANOVIC, Ivan DANYLIUK, Arobindu DASH, Daniela DI SANTO, Violeta ENEA, Daiane Gracieli FALLER, Gavan FITZSIMONS, Alexandra GHEORGHIU, Ángel GÓMEZ, Ali HAMAIDIA, Qing HAN, Mai HELMY, Joevarian HUDIYANA, Bertus F. JERONIMUS, Ding‐YU JIANG, Veljko JOVANOVIĆ, Željka KAMENOV, Anna KENDE, Shian‐Ling KENG, Tra Thi Thanh KIEU, Yasin KOC, Kamila KOVYAZINA, Inna KOZYTSKA, Joshua KRAUSE, Arie W. KRUGLANSKI, Anton KURAPOV, Maja KUTLACA, Nóra Anna LANTOS, Edward P. Jr LEMAY, Cokorda Bagus Java LESMANA, Winnifred R. LOUIS, Adrian LUEDERS, Najma Iqbal MALIK, Anton MARTINEZ, Kira O. MCCABE, Jasmina MEHULIĆ, Mirra Noor MILLA, Idris MOHAMMED, Erica MOLINARIO, Manuel MOYANO, Hayat MUHAMMAD, Silvana MULA, Hamdi MULUK, Solomiia MYRONIUK, Reza NAJAFI, Claudia F. NISA, Boglárka NYÚL, Paul A. O'KEEFE, Jose Javier Olivas OSUNA, Evgeny N. OSIN, Joonha PARK, Gennaro PICA, Antonio PIERRO, Jonas REES, Anne Margit REITSEMA, Elena RESTA, Marika RULLO, Michelle K. RYAN, Adil SAMEKIN, Pekka SANTTILA, Edyta SASIN, Birga Mareen SCHUMPE, Heyla A. SELIM, Michael Vicente STANTON, Samiah SULTANA, Eleftheria TSELIOU, Akira UTSUGI, Jolien Anne VAN BREEN, Kees VAN VEEN, Michelle R. VANDELLEN, Alexandra VAZQUEZ, Robin WOLLAST, Wai-Lan Victoria YEUNG, Somayeh ZAND, Iris L. ŽEŽELJ, Bang ZHENG, Andreas ZICK, Claudia ZÚÑIGA, N. Pontus LEANDER

Research output: Journal PublicationsJournal Article (refereed)peer-review

3 Citations (Scopus)

Abstract

Psychological research on the predictors of conspiracy theorizing—explaining important social and political events or circumstances as secret plots by malevolent groups—has flourished in recent years. However, research has typically examined only a small number of predictors in one, or a small number of, national contexts. Such approaches make it difficult to examine the relative importance of predictors, and risk overlooking some potentially relevant variables altogether. To overcome this limitation, the present study used machine learning to rank-order the importance of 115 individual- and country-level variables in predicting conspiracy theorizing. Data were collected from 56,072 respondents across 28 countries during the early weeks of the COVID-19 pandemic. Echoing previous findings, important predictors at the individual level included societal discontent, paranoia, and personal struggle. Contrary to prior research, important country-level predictors included indicators of political stability and effective government COVID response, which suggests that conspiracy theorizing may thrive in relatively well-functioning democracies.
Original languageEnglish
Pages (from-to)1191-1203
Number of pages13
JournalEuropean Journal of Social Psychology
Volume53
Issue number6
Early online date30 Jun 2023
DOIs
Publication statusPublished - Oct 2023

Bibliographical note

Funding Information:
The authors disclosed receipt of the following financial support for the research included in this article: New York University Abu Dhabi (VCDSF/75‐71015), University of Groningen (Sustainable Society & Ubbo Emmius Fund). Preparation of this article was also supported by the HORIZON EUROPE European Research Council Advanced Grant ‘Consequences of conspiracy theories ‐ CONSPIRACY_FX’ Number: 101018262 awarded to the first author.

Publisher Copyright:
© 2023 The Authors. European Journal of Social Psychology published by John Wiley & Sons Ltd.

Keywords

  • conspiracy theories
  • country-level variables
  • COVID-19
  • machine learning
  • individual-level variables

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