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differences in trying to generalize these findings (for example, to cultures that do not have as much trust in governments and corporations).

Until recently, many researchers had assumed that a fundamental parameter in the disclosure of location information is the degree of precision of the disclosure (i.e., whether the device discloses complete geographical coordinates or only an approximation, such as the city name). Consolvo et al.’s experience sampling study of a location-enhanced person finder, found however, that in most cases, participants did not ‘blur’ their location to avoid telling others where they were [65]. Instead, participants would either not respond at all, or provide the other person with the location information that they thought would be most meaningful to the recipient.

The findings of Kaasinen and Consolvo et al. diverge from common wisdom in the privacy community. We believe that these studies are compelling examples of why HCI research is important for furthering understanding of end-user privacy concerns.

3.2 Methodological Issues

In this section, we sketch out some of the methodological issues that arise when studying privacy preferences and concerns.

3.2.1 The Use of Surveys in Privacy Research

Surveys are typically used to probe general opinions about well-known applications (e.g., e-commerce), issues (e.g., identity theft), and concerns (e.g., loss of control). Surveys can be used to efficiently probe the preferences and opinions of large numbers of people, and can provide statistically significant and credible results. However, surveying privacy concerns presents the problem of conveying sufficient and unbiased information to non-expert users so that they can express reasonable and informed preferences. Risk analysis is hard even for experts, let alone individuals unfamiliar with a given domain or application. To address this problem, scenarios have been used to convey contextual information, and can greatly increase the effectiveness and credibility of survey responses, but at the risk of introducing significant bias.

A second limitation of privacy surveys, even those employing scenarios, is that they only collect participants’ attitudes, which may be quite different from actual behavior and thus not as useful for furthering understanding and aiding system design. To increase realism, Experience Sampling Method (ESM) studies can be used to probe individuals’ feelings, preferences and opinions in a specific setting [309]. Experience Sampling techniques are defined as interval-, signal- and event-contingent, depending on what initiates the self-report procedure (respectively, the elapsing of a predefined time interval, a signal provided by the researchers, or a specific event involving the participant).

Diaries are often used in conjunction with ESM for studying mobile technologies. For example, Barkhuus and Dey employed a diary to perform an interval-contingent study regarding the location disclosure preferences of possible location-based applications [35]. Colbert notes that in diary studies, “the participant is asked a hypothetical question about how they would react were their position information obtained, albeit contextualised in an actual rendezvous” [63]. However, without a working reference technology, recall errors and the hypothetical nature of questions may bias the results. For example,

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