Social media firestorms pose a significant challenge for firms in the digital age. Tackling firestorms is difficult because the judgments and responses from social media users are influenced by not only the nature of the transgressions but also by the reactions and opinions of other social media users. Drawing on the heuristic-systematic information processing model, we propose a research model to explain the effects of social impact (the heuristic mode) and argument quality and moral intensity (the systematic mode) on perceptions of firm wrongness (the judgment outcome) as well as the effects of perceptions of firm wrongness on vindictive complaining and patronage reduction. We adopted a mixed methods approach in our investigation, including a survey, an experiment, and a focus group study. Our findings show that the heuristic and systematic modes of information processing exert both direct and interaction effects on individuals’ judgment. Specifically, the heuristic mode of information processing dominates overall and also biases the systematic mode. Our study advances the literature by offering an alternative explanation for the emergence of social media firestorms and identifying a novel context in which the heuristic mode dominates in dual information processing. It also sheds light on the formulation of response strategies to mitigate the adverse impacts resulting from social media firestorms. We conclude our paper with limitations and future research directions.
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Active learning has become an increasingly popular method for screening large amounts of data in systematic reviews and meta-analyses. The active learning process continually improves its predictions on the remaining unlabeled records, with the goal of identifying all relevant records as early as possible. However, determining the optimal point at which to stop the active learning process is a challenge. The cost of additional labeling of records by the reviewer must be balanced against the cost of erroneous exclusions. This paper introduces the SAFE procedure, a practical and conservative set of stopping heuristics that offers a clear guideline for determining when to end the active learning process in screening software like ASReview. The eclectic mix of stopping heuristics helps to minimize the risk of missing relevant papers in the screening process. The proposed stopping heuristic balances the costs of continued screening with the risk of missing relevant records, providing a practical solution for reviewers to make informed decisions on when to stop screening. Although active learning can significantly enhance the quality and efficiency of screening, this method may be more applicable to certain types of datasets and problems. Ultimately, the decision to stop the active learning process depends on careful consideration of the trade-off between the costs of additional record labeling against the potential errors of the current model for the specific dataset and context.
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People tend to disclose personal identifiable information (PII) that could be used by cybercriminals against them. Often, persuasion techniques are used by cybercriminals to trick people to disclose PII. This research investigates whether people can be made less susceptible to persuasion by reciprocation (i.e., making people feel obligated to return a favour) and authority, particularly in regard to whether information security knowledge and positive affect moderate the relation between susceptibility to persuasion and disclosing PII. Data are used from a population-based survey experiment that measured the actual disclosure of PII in an experimental setting (N = 2426). The results demonstrate a persuasion–disclosure link, indicating that people disclose more PII when persuaded by reciprocation, but not by authority. Knowledge of information security was also found to relate to disclosure. People disclosed less PII when they possessed more knowledge of information security. Positive affect was not related to the disclosure of PII. And contrary to expectations, no moderating effects were found of information security knowledge nor positive affect on the persuasion–disclosure link. Possible explanations are discussed, as well as limitations and future research directions. Uitgegeven door Sage, APA beschrijving: van der Kleij, R., van ‘t Hoff—De Goede, S., van de Weijer, S., & Leukfeldt, R. (2023). Social engineering and the disclosure of personal identifiable information: Examining the relationship and moderating factors using a population-based survey experiment. Journal of Criminology, 56(2-3), 278-293. https://doi.org/10.1177/26338076231162660
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