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. BUTTRICK; Phatthanakit 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

doi:10.1002/ejsp.2968

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

Lingnan University

Research output: Journal Publications › Journal Article (refereed) › peer-review

7 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 language	English
Pages (from-to)	1191-1203
Number of pages	13
Journal	European Journal of Social Psychology
Volume	53
Issue number	6
Early online date	30 Jun 2023
DOIs	https://doi.org/10.1002/ejsp.2968
Publication status	Published - Oct 2023

Bibliographical note

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

Funding

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.

Keywords

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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https://onlinelibrary.wiley.com/doi/10.1002/ejsp.2968

Cite this

PsyCorona Study, DOUGLAS, K. M., SUTTON, R. M., VAN LISSA, C. J., STROEBE, W., KREIENKAMP, J., AGOSTINI, M., BÉLANGER, J. J., GÜTZKOW, B., ABAKOUMKIN, G., ABDUL KHAIYOM, J. H., AHMEDI, V., AKKAS, H., ALMENARA, C. A., ATTA, M., BAGCI, S. C., BASEL, S., BERISHA KIDA, E., BERNARDO, A. B. I., ... LEANDER, N. P. (2023). Identifying important individual- and country-level predictors of conspiracy theorizing : A machine learning analysis. European Journal of Social Psychology, 53(6), 1191-1203. https://doi.org/10.1002/ejsp.2968

@article{fefce506b70c41d9b0b5487fc65c85b8,

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

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.",

keywords = "conspiracy theories, country-level variables, COVID-19, machine learning, individual-level variables",

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

note = "Publisher Copyright: {\textcopyright} 2023 The Authors. European Journal of Social Psychology published by John Wiley & Sons Ltd.",

year = "2023",

month = oct,

doi = "10.1002/ejsp.2968",

language = "English",

volume = "53",

pages = "1191--1203",

journal = "European Journal of Social Psychology",

issn = "0046-2772",

publisher = "John Wiley & Sons Ltd.",

number = "6",

}

PsyCorona Study, DOUGLAS, KM, SUTTON, RM, VAN LISSA, CJ, STROEBE, W, KREIENKAMP, J, AGOSTINI, M, BÉLANGER, JJ, GÜTZKOW, B, ABAKOUMKIN, G, ABDUL KHAIYOM, JH, AHMEDI, V, AKKAS, H, ALMENARA, CA, ATTA, M, BAGCI, SC, BASEL, S, BERISHA KIDA, E, BERNARDO, ABI, BUTTRICK, NR, CHOBTHAMKIT, P, CHOI, HS, CRISTEA, M, CSABA, S, DAMNJANOVIC, K, DANYLIUK, I, DASH, A, DI SANTO, D, ENEA, V, FALLER, DG, FITZSIMONS, G, GHEORGHIU, A, GÓMEZ, Á, HAMAIDIA, A, HAN, Q, HELMY, M, HUDIYANA, J, JERONIMUS, BF, JIANG, DYU, JOVANOVIĆ, V, KAMENOV, Ž, KENDE, A, KENG, SL, KIEU, TTT, KOC, Y, KOVYAZINA, K, KOZYTSKA, I, KRAUSE, J, KRUGLANSKI, AW, KURAPOV, A, KUTLACA, M, LANTOS, NA, LEMAY, EPJ, LESMANA, CBJ, LOUIS, WR, LUEDERS, A, MALIK, NI, MARTINEZ, A, MCCABE, KO, MEHULIĆ, J, MILLA, MN, MOHAMMED, I, MOLINARIO, E, MOYANO, M, MUHAMMAD, H, MULA, S, MULUK, H, MYRONIUK, S, NAJAFI, R, NISA, CF, NYÚL, B, O'KEEFE, PA, OSUNA, JJO, OSIN, EN, PARK, J, PICA, G, PIERRO, A, REES, J, REITSEMA, AM, RESTA, E, RULLO, M, RYAN, MK, SAMEKIN, A, SANTTILA, P, SASIN, E, SCHUMPE, BM, SELIM, HA, STANTON, MV, SULTANA, S, TSELIOU, E, UTSUGI, A, VAN BREEN, JA, VAN VEEN, K, VANDELLEN, MR, VAZQUEZ, A, WOLLAST, R, YEUNG, W-LV, ZAND, S, ŽEŽELJ, IL, ZHENG, B, ZICK, A, ZÚÑIGA, C & LEANDER, NP 2023, 'Identifying important individual- and country-level predictors of conspiracy theorizing : A machine learning analysis', European Journal of Social Psychology, vol. 53, no. 6, pp. 1191-1203. https://doi.org/10.1002/ejsp.2968

TY - JOUR

T1 - Identifying important individual- and country-level predictors of conspiracy theorizing : A machine learning analysis

AU - PsyCorona Study

AU - DOUGLAS, Karen M.

AU - SUTTON, Robbie M.

AU - VAN LISSA, Caspar J.

AU - STROEBE, Wolfgang

AU - KREIENKAMP, Jannis

AU - AGOSTINI, Maximilian

AU - BÉLANGER, Jocelyn J.

AU - GÜTZKOW, Ben

AU - ABAKOUMKIN, Georgios

AU - ABDUL KHAIYOM, Jamilah Hanum

AU - AHMEDI, Vjollca

AU - AKKAS, Handan

AU - ALMENARA, Carlos A.

AU - ATTA, Mohsin

AU - BAGCI, Sabahat Cigdem

AU - BASEL, Sima

AU - BERISHA KIDA, Edona

AU - BERNARDO, Allan B. I.

AU - BUTTRICK, Nicholas R.

AU - CHOBTHAMKIT, Phatthanakit

AU - CHOI, Hoon‐Seok

AU - CRISTEA, Mioara

AU - CSABA, Sára

AU - DAMNJANOVIC, Kaja

AU - DANYLIUK, Ivan

AU - DASH, Arobindu

AU - DI SANTO, Daniela

AU - ENEA, Violeta

AU - FALLER, Daiane Gracieli

AU - FITZSIMONS, Gavan

AU - GHEORGHIU, Alexandra

AU - GÓMEZ, Ángel

AU - HAMAIDIA, Ali

AU - HAN, Qing

AU - HELMY, Mai

AU - HUDIYANA, Joevarian

AU - JERONIMUS, Bertus F.

AU - JIANG, Ding‐YU

AU - JOVANOVIĆ, Veljko

AU - KAMENOV, Željka

AU - KENDE, Anna

AU - KENG, Shian‐Ling

AU - KIEU, Tra Thi Thanh

AU - KOC, Yasin

AU - KOVYAZINA, Kamila

AU - KOZYTSKA, Inna

AU - KRAUSE, Joshua

AU - KRUGLANSKI, Arie W.

AU - KURAPOV, Anton

AU - KUTLACA, Maja

AU - LANTOS, Nóra Anna

AU - LEMAY, Edward P. Jr

AU - LESMANA, Cokorda Bagus Java

AU - LOUIS, Winnifred R.

AU - LUEDERS, Adrian

AU - MALIK, Najma Iqbal

AU - MARTINEZ, Anton

AU - MCCABE, Kira O.

AU - MEHULIĆ, Jasmina

AU - MILLA, Mirra Noor

AU - MOHAMMED, Idris

AU - MOLINARIO, Erica

AU - MOYANO, Manuel

AU - MUHAMMAD, Hayat

AU - MULA, Silvana

AU - MULUK, Hamdi

AU - MYRONIUK, Solomiia

AU - NAJAFI, Reza

AU - NISA, Claudia F.

AU - NYÚL, Boglárka

AU - O'KEEFE, Paul A.

AU - OSUNA, Jose Javier Olivas

AU - OSIN, Evgeny N.

AU - PARK, Joonha

AU - PICA, Gennaro

AU - PIERRO, Antonio

AU - REES, Jonas

AU - REITSEMA, Anne Margit

AU - RESTA, Elena

AU - RULLO, Marika

AU - RYAN, Michelle K.

AU - SAMEKIN, Adil

AU - SANTTILA, Pekka

AU - SASIN, Edyta

AU - SCHUMPE, Birga Mareen

AU - SELIM, Heyla A.

AU - STANTON, Michael Vicente

AU - SULTANA, Samiah

AU - TSELIOU, Eleftheria

AU - UTSUGI, Akira

AU - VAN BREEN, Jolien Anne

AU - VAN VEEN, Kees

AU - VANDELLEN, Michelle R.

AU - VAZQUEZ, Alexandra

AU - WOLLAST, Robin

AU - YEUNG, Wai-Lan Victoria

AU - ZAND, Somayeh

AU - ŽEŽELJ, Iris L.

AU - ZHENG, Bang

AU - ZICK, Andreas

AU - ZÚÑIGA, Claudia

AU - LEANDER, N. Pontus

PY - 2023/10

Y1 - 2023/10

N2 - 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.

AB - 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.

KW - conspiracy theories

KW - country-level variables

KW - COVID-19

KW - machine learning

KW - individual-level variables

UR - http://www.scopus.com/inward/record.url?scp=85164174460&partnerID=8YFLogxK

U2 - 10.1002/ejsp.2968

DO - 10.1002/ejsp.2968

M3 - Journal Article (refereed)

SN - 0046-2772

VL - 53

SP - 1191

EP - 1203

JO - European Journal of Social Psychology

JF - European Journal of Social Psychology

IS - 6

ER -

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

Abstract

Bibliographical note

Funding

Keywords

UN SDGs

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