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

Douglas, Karen M. and Sutton, Robbie M. and Van Lissa, Caspar J. and Stroebe, Wolfgang and Kreienkamp, Jannis and Agostini, Maximilian and Bélanger, Jocelyn J. and Gützkow, Ben and Abakoumkin, Georgios and Khaiyom, Jamilah Hanum Abdul and Ahmedi, Vjollca and Akkas, Handan and Almenara, Carlos A. and Atta, Mohsin and Bağcı, Çiğdem and Basel, Sima and Berisha Kida, Edona and Bernardo, Allan B.I. and Buttrick, Nicholas R. and Chobthamkit, Phatthanakit and Choi, Hoon Seok and Cristea, Mioara and Csaba, Sára and Damnjanovic, Kaja and Danyliuk, Ivan and Dash, Arobindu and Di Santo, Daniela and Enea, Violeta and Faller, Daiane Gracieli and Fitzsimons, Gavan and Gheorghiu, Alexandra and Gómez, Ángel and Hamaidia, Ali and Han, Qing and Helmy, Mai and Hudiyana, Joevarian and Jeronimus, Bertus F. and Yu Jiang, Ding and Jovanović, Veljko and Kamenov, Željka and Kende, Anna and Keng, Shian Ling and Kieu, Tra Thi Thanh and Koc, Yasin and Kovyazina, Kamila and Kozytska, Inna and Krause, Joshua and Kruglanski, Arie W. and Kurapov, Anton and Kutlaca, Maja and Lantos, Nóra Anna and Lemay, Edward P. and Lesmana, Cokorda Bagus Jaya and Louis, Winnifred R. and Lueders, Adrian and Malik, Najma Iqbal and Martinez, Anton and McCabe, Kira O. and Mehulić, Jasmina and Milla, Mirra Noor and Mohammed, Idris and Molinario, Erica and Moyano, Manuel and Muhammad, Hayat and Mula, Silvana and Muluk, Hamdi and Myroniuk, Solomiia and Najafi, Reza and Nisa, Claudia F. and Nyúl, Boglárka and O'Keefe, Paul A. and Olivas Osuna, Jose Javier and Osin, Evgeny N. and Park, Joonha and Pica, Gennaro and Pierro, Antonio and Rees, Jonas and Reitsema, Anne Margit and Resta, Elena and Rullo, Marika and Ryan, Michelle K. and Samekin, Adil and Santtila, Pekka and Sasin, Edyta and Schumpe, Birga M. and Selim, Heyla A. and Stanton, Michael Vicente and Sultana, Samiah and Tseliou, Eleftheria and Utsugi, Akira and van Breen, Jolien Anne and Van Veen, Kees and vanDellen, Michelle R. and Vázquez, Alexandra and Wollast, Robin and Yeung, Victoria Wai Lan and Zand, Somayeh and Žeželj, Iris L. and Zheng, Bang and Zick, Andreas and Zúñiga, Claudia and Leander, N. Pontus (2023) Identifying important individual- and country-level predictors of conspiracy theorizing: a machine learning analysis. European Journal of Social Psychology, 53 (6). pp. 1191-1203. ISSN 0046-2772 (Print) 1099-0992 (Online)

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Official URL: https://dx.doi.org/10.1002/ejsp.2968

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.

Item Type:	Article
Uncontrolled Keywords:	conspiracy theories; country-level variables; COVID-19; individual-level variables; machine learning
Divisions:	Faculty of Arts and Social Sciences
Depositing User:	Çiğdem Bağcı
Date Deposited:	25 Sep 2024 15:00
Last Modified:	25 Sep 2024 15:00
URI:	https://research.sabanciuniv.edu/id/eprint/50139

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Identifying important individual- and country-level predictors of conspiracy theorizing: a machine learning analysis. (deposited 07 Aug 2023 16:59)
- Identifying important individual- and country-level predictors of conspiracy theorizing: a machine learning analysis. (deposited 25 Sep 2024 15:00) [Currently Displayed]

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