Something That Turns You On. Don't Make Me Wait. Heart In Your Life. Watching You, Watching Me. Finally, a mixed response case included both positive and negative emotions, along with three positive and three negative comments. To ensure that participants noticed the manipulation, we included five statements at the end of the questionnaire and asked participants to indicate the extent of their agreement on a scale of 1 disagree to 5 agree: In all but the last case, the differences among groups were significant and conformed to the anticipated directions for means and std.
The order of scales was randomized across participants and ANOVA was conducted to test the hypothesis. Figure 4 presents the means and standard errors of all dependent variables, according to experimental case. Participants in the positive case group perceived a greater number of advantages to self-disclosure behavior in comparison to the negative case and the mixed case while those in the negative case group reported the opposite in comparison to the control group and positive case group.
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Means and standard errors: Scale ranges from 1 not at all to 5 a lot. We also observed correlations among the three dependent variables. In the current study, the correlation between SD tendency and perceived gains remains much stronger than the one between SD tendency and perceived losses gains: Most of these hypotheses were largely supported by empirical data: Moreover, perceived gains were positively correlated with SD behavior.
Only partial confirmation was obtained concerning losses, however: While a significant association was found between perceived losses to self and to others, the applied manipulation did not alter perception and no effects on behavior were noted. We conceptualized a model that underscores three key mechanisms at work: If significant others disclose information plentifully, users are likely to adopt such patterns and disclose more.
To date, their hypothesis has not been tested empirically. We attempted to advance this discussion by focussing on aspects of social influence that ought to be accorded more attention in an age of networked media: We were thus able to shed new light on the complex effect of social influence of risk assessment on disclosure behavior. The situation differs with regard to perception of losses. In fact, manipulation influenced assessment of gains and not of losses.
These findings are in line with existing scholarship indicating that although users ascribe high risk levels to SD lack of safety, security, reliability and trustworthiness , they still disclose a considerable amount of apparently sensitive information e. We suggest two reasons that might explain the difference between the predictive power of gains and losses on SD.
First, as noted by Ellison et al. In Ellison et al. SNS users must respond in a manner that leaves an observable marker of attention as a way of cultivating, or grooming, their connections. We argue that this perception of the rewards other users are supposedly receiving is among the factors that motivate Facebook users to disclose information liberally.
Another possible reason for the observed disparity concerns our approach to studying risk assessment in connection with SD on Facebook.
Our findings suggest that in the case of perceived gains, the significance and likelihood of the gain have a similar effect on SD, but when it comes to losses, the picture is more complex: The significance of a given loss is negatively correlated with SD, whereas the likelihood of a given loss is positively correlated with it. This may well reflect the complexity of risk-assessment as it applies to SD on Facebook: Those who attribute significant losses to SD on Facebook will be less likely to self-disclose, regardless of their perceived likelihood of these losses.
By contrast, those who disclose more may realize that these activities increase their chances of being harmed, but they might not necessarily perceive the possible losses as significant. Several aspects of the research design may well have affected the findings of this study. Measures, for example, may constitute a significant source of bias.
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To reinforce design, we supplemented the survey with an experiment. Although the resulting combination provides powerful methodical strength, alternative designs could have been considered as well, such as a study of organic interactions on Facebook, analyzing the interplay between visible social information and behavior patterns, made possible by the advent of unobtrusive behavioral measurement.
Its advantages notwithstanding, this method also entails certain constraints, particularly ethical concerns: Furthermore, this study used an opt-in sampling method, wherein participants selected themselves. Obviously, a non-random sample of paid participants would engender various biases. Considering the extremely low response rates prevailing at present, however, the method appeared particularly useful despite its limitations. Another constraint worth mentioning involved the characteristics of the scales used.
For example, we asked participants if they share personal information on Facebook, but did not specify whether this information contains a phone number, an email address, a password, etc.
Clearly, while users might be willing to share phone numbers, they would not necessarily agree to sharing passwords. Future studies could focus on specific SD behavior and nuance our scales. Several additional factors may have exerted a substantive effect on results. For example, the sample was limited in two respects, as it comprised Israeli users alone and was tailored to one platform only—Facebook. Such replication could also be useful in countries whose privacy regulations and concerns differ from those of Israel.
Considering the well-documented dissimilarities among countries see, e. Studies of this kind might provide more intensive insight into the effects of culture on cost-benefit analysis and resulting SD behavior. Our sample comprises users of different ages see discussion in the Methodology section , as we sought to provide a representative nationwide sample of Facebook users to whatever extent possible—demographic information concerning Facebook users is not available to the public. It may be valuable, however, to conduct a comparative study with cohorts representing different age groups Generation Y and the older Generation X and Baby Boomers.
As an increasing number of studies show that privacy concerns among young people differ from the anxieties manifested by adults, subsequent studies could shed considerable light on the manner in which participant age affects the value ascribed to SNS losses and gains.
In this study, we did not distinguish between strong tie and weak tie friends. Realizing that social tie strength might influence OL, it could be valuable to conduct a study that explores the extent to which it does so. The study might also contribute to practice-led research. One issue that received massive attention by both researchers and practitioners is means of fostering privacy literacy in the context of online networked technologies, particularly on SNSs.
At present, Facebook responds to this challenge by sending its users personal reminders to review their privacy settings. It shows that the observation mechanism contributes to reward envy , that leads, in turn, to a high level of online SD. Subsequent studies could apply the model to examine the effects of OL on various manifestations of human conduct in online spaces.
To validate our measurements, we tested their correlations with related concepts on an additional sample, relying on previous research by Dienlin and Metzger , who developed scales to measure Facebook benefits, privacy concerns, Facebook privacy self-efficacy, Facebook self-disclosure and Facebook self-withdrawal. Furthermore, to validate data about self-disclosure, we asked participants to provide us with their Facebook activity log and added an item measuring passive Facebook use demonstrating distinction between self-disclosure and passive use.
In addition, developing the above measures, we also asked participants about their Facebook benefits, privacy concerns, Facebook privacy self-efficacy, Facebook self-disclosure and Facebook self-withdrawal. All scales are taken from Dienlin and Metzger full scales: Facebook allows users to download a log documenting all their activities. Nevertheless, it is important to note that participants did not comply with this request, resulting in a high attrition rate.
Furthermore, 22 participants failed to follow the instructions and thus supplied incorrect data. Seeking a uniform size indicator for all files photos, posts, events, friends, etc. As indicated, all items in our scales were loaded on one factor, except for the SD acts scale, for which a two-factor solution was identified: SD acts were loaded on one factor and another measuring passive use was loaded on another.
Only one item displayed high loadings of both factors: Perceived losses were correlated with Facebook self-withdrawal and privacy concerns. Percent refers to the percentage of participants for each scale. Perceived gains are measured as the likelihood of gain on a scale of 1—5 weighted by its magnitude on a 1—5 scale.
Perceived losses measured as the likelihood of loss on a scale of 1—5 weighted by its magnitude on a scale of 1—5. Other SNS use hrs. Table 1 Results of Contrast between Experimental Conditions. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.
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Close mobile search navigation Article navigation. Theoretical framework and hypotheses: The effects of social observation on technology perception and use. Limitations and future research directions. Distribution of Risk Assessment Measures. Watching Me Watching You: Oranim Academic College, Israel. View large Download slide. SEM of SD behavior social learning. Ultra-Orthodox Jews, who comprise 8. Because of language barriers, the Israeli Arab population was not included in the sample.
We chose to present a certain degree of social response, given that typically any post receives some attention, thus a post with no response at all may appear unrealistic.
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