Online privacy research has seen a focus on user behavior over the last decade, partly to understand and explain user decision-making and seeming inconsistencies regarding users' stated preferences. This article investigates the level of modeling that contemporary approaches rely on to explain said inconsistencies and whether drawn conclusions are justified by the applied modeling methodology. Additionally, it provides resources for researchers interested in using computational modeling.,The article uses data from a pre-existing literature review on the privacy paradox (N = 179 articles) to identify three characteristics of prior research: (1) the frequency of references to computational-level theories of human decision-making and perception in the literature, (2) the frequency of interpretations of human decision-making based on computational-level theories, and (3) the frequency of actual computational-level modeling implementations.,After excluding unrelated articles, 44.1 percent of investigated articles reference at least one theory that has been traditionally interpreted on a computational level. 33.1 percent of all relevant articles make statements regarding computational properties of human cognition in online privacy scenarios. Meanwhile, 5.1 percent of all relevant articles apply formalized computational-level modeling to substantiate their claims.,The findings highlight the importance of formal, computational-level modeling in online privacy research, which has so far drawn computational-level conclusions without utilizing appropriate modeling techniques. Furthermore, this article provides an overview of said modeling techniques and their benefits to researchers, as well as references for model theories and resources for practical implementation.

中文翻译：

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形式化计算模型对于了解在线隐私研究中的用户行为的好处

过去十年来，在线隐私研究将重点放在用户行为上，部分目的是理解和解释用户决策以及与用户陈述的偏好有关的表象不一致。本文研究了当代方法用来解释上述不一致之处的建模水平，以及所得出的结论是否适用的建模方法是合理的。此外，它还为有兴趣使用计算建模的研究人员提供了资源。本文使用有关隐私悖论的现有文献综述的数据（N = 179篇文章）来确定先前研究的三个特征：（1）引用频率到文献中人类决策和感知的计算级理论，（2）基于计算级别理论的人类决策解释频率，以及（3）实际计算级别建模实现的频率。在排除无关文章之后，有44.1％的被调查文章引用了至少一种理论传统上是在计算级别上解释的。在所有相关文章中，有33.1％的人发表有关在线隐私场景中人类认知的计算属性的陈述。同时，所有相关文章中有5.1％的应用形式化计算级别建模来证实其主张。研究结果突显了形式化，计算级别建模在在线隐私研究中的重要性，到目前为止，该模型在没有利用适当建模的情况下得出了计算级别结论。技术。此外，