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Terrorist threats and attacks provide major risks and sources of public crises in the 21st century. New probabilistic computing technologies possess the capability of increasing the success of identifying terrorist threats and solving cybersecurity and encryption problems more efficiently. However, to identify terrorist threats, these technologies would require the use of a large amount of personal data, which cause potential concerns for privacy. We offer a social-identity explanation of public support for the detection of terrorist threats through the use of online personal data. A survey study (N = 1,204) revealed strong support for the provided social-identity explanation of public perceptions. As expected, respondents displayed in-group favoritism by more strongly supporting the use of private personal information from out-group members (non-U.S. citizens) than from in-group members (U.S. citizens). The observed in-group favoritism was most pronounced when respondents had both a strong national identity and a strong sense of general privacy concern. The observed differences were independent of respondents’ political orientation and age.


This is the published version of the Reimer, T., & Johnson, N. (2023). When Those With Privacy Concerns Show Stronger In-Group Favoritism: Using Personal Information From In-Group and Out-Group Members to Identify Terrorist Threats. SAGE Open, 13(3).