Example Plot for Assumed Relationships.

Example Plot for Assumed Relationships.

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Rational models of privacy self-management such as privacy calculus assume that sharing personal information online can be explained by individuals’ perceptions of risks and benefits. Previous research tested this assumption by conducting conventional multivariate procedures, including path analysis or structural equation modeling. However, these a...

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Context 1
... rather than merely interpreting the coefficients of the polynomial regression, in RSA the polynomial regression coefficients are used to create a three-dimensional plot depicting how two predictors relate to the outcome, and to compute response surface values. In other words, these parameters are used to examine a three-dimensional representation of the relationship between the predictors and the outcome (Edwards & Parry, 1993; for an example, see Figure 1). ...
Context 2
... response surfaces have several properties that can be used to make inferences. The line of congruence (LOC; blue line in Figure 1) is mathematically represented by the parameters a1 (i.e., b1 + b2) and a2 (b3 + b4 + b5). It is the line where the two predictors have the same values (i.e., X = Y). ...
Context 3
... the line of incongruence (LOIC; red line in Figure 1) addresses situations when the two predictors have opposite values (i.e., X = −Y). LOIC is represented by the parameters a3 (i.e., b1 − b2) and a4 (i.e., b3 − b4 + b5). ...
Context 4
... we expect a significant linear line of incongruency along with a non-significant line of congruence (i.e., significant a3 and non-significant a1, a2, and a4). Figure 1 visualizes this relationship. For instance, we expect that sharing behavior is at its highest (i.e., +2) for a participant that scored +2 on benefits and −2 on concerns, whereas the outcome is at its lowest (i.e., −2) for another participant that scored −2 on benefits and +2 on concerns. ...
Context 5
... in Dataset 2, the positive a3 indicates that participants reported (the willingness for) sharing more information online when their anticipated benefits were higher than their concern for their privacy (compared to the other way around). At the same time, unlike in Dataset 2, the positive a1 indicates that the outcome variables (i.e., selfreported self-disclosure on Twitter in Dataset 1 and the willingness for future online self-disclosure in Dataset 3) were greatest when both benefits and concerns about privacy were high (see Table 2 and Figure 1 for the parameters and plots). Note. ...

Citations

... Users go for self-disclose more in case their gratifications surpass privacy concerns. This means gratifications play a crucial role while making a choice to disclose information (Kezer, Dienlin, & Baruh, 2022). ...
Article
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The constantly evolving world and the advent of social media gave birth to excessive digitalized human interaction enhancing connectivity among users. These new modes of interaction added to the excitement of sharing, but at the same time it has placed some concerns about the excessive sharing of personal information on digital platforms. The boundaries of subsequent privacy violations are critical concerns in the advance of the technological age. Pakistan is a country with an enormously growing number of internet users, from diverse socio-cultural backgrounds and the platforms are used for distinctive reasons, resulting in millions of posts every minute of the day. A qualitative approach of in-depth interviews was used for the study. Considering the qualitative nature of the study interviews was conducted based on the semi-structured questionnaire. The sample using a purposive sampling technique included users for the sake of highlighting the privacy concerns and experts like media academics, psychologists, lawyers, representatives from the cyber-crime wing of FIA, and the country representatives of social media platforms for understanding the approaches to bridge the gaps regarding those concerns. Social media representatives ensured users' sense of security as a priority of social platforms. Users' inferences and privacy awareness were also gauged which showed concerns about the layout of privacy policies. The privacy calculus approach helped understand the user's psyche of disclosure while having privacy concerns.