Examining American and Chinese Internet Users' Contextual Privacy Preferences of Behavioral Advertising

Wang, Yang; Xia, Huichuan; Huang, Yun

doi:10.1145/2818048.2819941

Cited by 33 publications

(17 citation statements)

References 37 publications

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“…Their estimated mean RSeBIS score is lower by about 9 than that of the American participants. Our results align with previous work that shows that Asian users are likely to be less concerned about online privacy, to exhibit less private behavior online, and not to use phone lockingmechanisms, than their western counterparts (e.g., [22,29,35,53]).…”

Section: Culturesupporting

confidence: 91%

“…Cross-cultural studies in the area of computer security and privacy studied the differences in privacy concerns and behavior between different cultures and explored the reasons underlying these differences (e.g., [2,3,12,32,53,57]). For example, Almakrami compared the self-disclosure practices of Saudis on Facebook with those of Australians [2].…”

Section: Culture In Computer Security and Privacymentioning

confidence: 99%

“…Various research efforts compared the privacy (but not security) concerns of Internet users from Asian countries with those of their counterparts from western countries [27,29,34,35,53,52,57]. In general, most of these efforts concluded that the Asian users are less concerned about their online privacy than users from western countries.…”

Section: Culture In Computer Security and Privacymentioning

confidence: 99%

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Self-Confidence Trumps Knowledge

Sawaya

Sharif

Christin

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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Computer security tools usually provide universal solutions without taking user characteristics (origin, income level, ...) into account. In this paper, we test the validity of using such universal security defenses, with a particular focus on culture. We apply the previously proposed Security Behavior Intentions Scale (SeBIS) to 3,500 participants from seven countries. We first translate the scale into seven languages while preserving its reliability and structure validity. We then build a regression model to study which factors affect participants' security behavior. We find that participants from different countries exhibit different behavior. For instance, participants from Asian countries, and especially Japan, tend to exhibit less secure behavior. Surprisingly to us, we also find that actual knowledge influences user behavior much less than user self-confidence in their computer security knowledge. Stated differently, what people think they know affects their security behavior more than what they do know.

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Section: Culturesupporting

confidence: 91%

Section: Culture In Computer Security and Privacymentioning

confidence: 99%

Section: Culture In Computer Security and Privacymentioning

confidence: 99%

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Self-Confidence Trumps Knowledge

Sawaya

Sharif

Christin

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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“…Perhaps the most common-sense understanding of privacy in the literature is that it is about the ability to control the flow of personal data. Often attributed to legal scholar Alan Westin (1967), this notion is articulated in various ways, including the extent to which individuals, groups, or institutions may control when, how, and to what extent information about them is: shared with others (Tang et al 2011), known to others (Wang et al 2016), or communicated to others (Page et al 2013). The control thesis may also be applied to how information and its visibility is limited (Shoemaker andInkpen 2001, Williamson et al 2010), filtered (Smith et al 2012), directed (Gorm and Shklovski 2016), or used (Karat et al 2006).…”

Section: Privacy In (Some Of) the Design Literaturementioning

confidence: 99%

Repacking ‘Privacy’ for a Networked World

Crabtree

Tolmie

Knight

2017

Comput Supported Coop Work

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Abstract. In this paper we examine the notion of privacy as promoted in the digital economy and how it has been taken up as a design challenge in the fields of CSCW, HCI and Ubiquitous Computing. Against these prevalent views we present an ethnomethodological study of digital privacy practices in 20 homes in the UK and France, concentrating in particular upon people's use of passwords, their management of digital content, and the controls they exercise over the extent to which the online world at large can penetrate their everyday lives. In explicating digital privacy practices in the home we find an abiding methodological concern amongst members to manage the potential 'attack surface' of the digital on everyday life occasioned by interaction in and with the networked world. We also find, as a feature of this methodological preoccupation, that privacy dissolves into a heterogeneous array of relationship management practices. Accordingly we propose that 'privacy' has little utility as a focus for design, and suggest instead that a more productive way forward would be to concentrate on supporting people's evident interest in managing their relationships in and with the networked world.

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“…These studies do not explicitly specify "privacy expectation" in the study. Some of the studies elicit users' privacy preferences (Olson et al, 2005;Leon et al, 2013;Wang et al, 2016;Naeini et al, 2017). By measuring preferences, they may be implicitly measuring privacy expectation in the desired sense.…”

Section: Empirical Studies On Privacy Expectationmentioning

confidence: 99%

Types of Privacy Expectations

Rao

2020

Front. Big Data

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Understanding user privacy expectations is important and challenging. General Data Protection Regulation (GDPR) for instance requires companies to assess user privacy expectations. Existing privacy literature has largely considered privacy expectation as a single-level construct. We show that it is a multi-level construct and people have distinct types of privacy expectations. Furthermore, the types represent distinct levels of user privacy, and, hence, there can be an ordering among the types. Inspired by expectations-related theory in non-privacy literature, we propose a conceptual model of privacy expectation with four distinct types-Desired, Predicted, Deserved and Minimum. We validate our proposed model using an empirical within-subjects study that examines the effect of privacy expectation types on participant ratings of privacy expectation in a scenario involving collection of health-related browsing activity by a bank. Results from a stratified random sample (N = 1,249), representative of United States online population (±2.8%), confirm that people have distinct types of privacy expectations. About one third of the population rates the Predicted and Minimum expectation types differently, and differences are more pronounced between younger (18-29 years) and older (60+ years) population. Therefore, studies measuring privacy expectations must explicitly account for different types of privacy expectations.

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Examining American and Chinese Internet Users' Contextual Privacy Preferences of Behavioral Advertising

Cited by 33 publications

References 37 publications

Self-Confidence Trumps Knowledge

Self-Confidence Trumps Knowledge

Repacking ‘Privacy’ for a Networked World

Types of Privacy Expectations

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