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Abstract
Advancements in big data analytics offer new avenues for the analysis and deciphering of suspicious activities on the internet. One promising new technology to increase the identification of terrorism threats is based on probabilistic computing. The technology promises to provide more efficient problem solutions in encryption and cybersecurity. Probabilistic computing technologies use large amounts of data, though, which raises potential privacy concerns. A study (N = 1,023) was conducted to survey public support for using probabilistic computing technologies to increase counterterrorism efforts. Overall, strong support was found for the use of publicly available personal information (e.g., personal websites). Regarding private personal information (e.g., online conversations), respondents perceived it to be more appropriate to use information from out-group members (non-American citizens) than from in-group members (American citizens). In line with a social-identity account, this form of in-group favoritism was strongest among respondents displaying a combination of strong national identities and strong privacy concerns.
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