Replication Data for: Information Access Under Restrictions: Drivers of Circumvention Tool Use

DOI

This is an online survey data from Iranian Telegram users. The abstract of the article in which this data has been used is as follows. State-imposed internet censorship has expanded globally, leading many users to rely on circumvention tools to access restricted platforms. In Iran, where Telegram remains heavily filtered, identifying the factors that shape circumvention behavior is key to understanding digital resistance. This study examines sociodemographic and attitudinal predictors of circumvention tool use among Iranian Telegram users, drawing on an online survey of 517 participants. Ten variables related to political engagement, psychological reactance, media perceptions, and individual characteristics were analyzed. Regression results identify six significant predictors: gender, political interest, motivated resistance to censorship, endorsement of censorship, religiosity, and perceived similarity to state media. Men, politically interested users, and individuals displaying higher reactance are more likely to bypass restrictions, while support for censorship and greater alignment with government messaging reduce circumvention. Age, education, trust, and use of state media show no significant effect. Overall, psychological and political orientations strongly shape digital resistance in restrictive media environments.

SPSS, 28

Identifier
DOI https://doi.org/10.18710/2ZC2CZ
Metadata Access https://dataverse.no/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18710/2ZC2CZ
Provenance
Creator Khosrowjerdi, Mahmood ORCID logo; Keshavarz, Hamid (ORCID: 0000-0002-5589-238X); Rak, Dorota ORCID logo; Jafari, Houman ORCID logo
Publisher DataverseNO
Contributor Khosrowjerdi, Mahmood; University of Inland Norway
Publication Year 2026
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact Khosrowjerdi, Mahmood (University of Inland Norway)
Representation
Resource Type Online survey data; Dataset
Format text/plain; application/pdf; text/x-fixed-field; application/x-spss-sav
Size 8199; 386031; 46150; 39069
Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Humanities; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences