Beyond the Privacy Paradox: A Cross-Cultural Study of Users’ Privacy-Related Decisions in the Social Networking Context

Abstract

The advent of Social Networking Sites (SNSs) during the past decade has encouraged individuals to intensively and voluntarily share enormous quantities of personal data. Users’ privacy concerns have been a subject of heated discussion. Users’ privacy concerns have been considered as an important predictor of their information disclosure practices in SNSs. However, a phenomenon identified as the Privacy Paradox suggests that there is no relationship between users’ privacy concerns (attitude) and their information disclosure practices (behaviour). The privacy paradox phenomenon has been discussed in the literature with conflicting findings. The ambiguity surrounding privacy practices and perceptions presents a challenge in designing platforms that prioritize privacy and prevent privacy abuses. Therefore, understanding users’ privacy-related decisions can provide useful insights into the design nature of such platforms. Consequently, this thesis aims at untangling the complicated nature and underlying mechanisms of users’ privacy-related decisions in SNSs by constructing and validating a theoretical research model. Moreover, given that culture significantly shapes users' privacy perceptions and practices, our study explores two distinct cultural perspectives. We illuminate the Western viewpoint on privacy through the United Kingdom's population and explore the non-Western Arabic culture through the Saudi Arabia's population. This thesis employs a sequential mixed-methods approach, encompassing the collection and analysis of both quantitative and qualitative data through four phases. Initially, a systematic literature review was carried out to develop a foundational framework and then a research model was created in light with this framework and Communication Privacy Management (CPM) theory. In the second phase, semi-structured interviews with privacy experts were undertaken to initially validate and improve the proposed model. In the third phase, our model was validated statistically through a large-scale quantitative approach, wherein data was collected from 709 participants from both cultures via an online questionnaire. Structural Equation Modelling (SEM) statistical technique was used to validate the model, assess the hypothesis and highlight cultural differences. In the fourth phase, follow-up interviews were conducted with 20 SNSs users form both cultures to understand the rationale behind their privacy-related decisions, and to clarify the obtained quantitative findings. Our findings illuminate how SNSs users balance two conflicting practices, online privacy and information disclosure to achieve the perceived benefits, highlighting users’ “protective self- presentation”. Interestingly, SNSs users employ different strategies to protect their online privacy and mitigate their concerns, while keep disclosing enough information to balance between the associated costs and benefits. Therfore, our study offers a potential explanation for the privacy paradox phenomenon. It provided an evidence that users employ a diverse range of privacy protection strategies to meet their privacy requirements. This extends beyond the simple binary choices of whether to disclose information or not, incorporating self-developed strategies (not system-based). Moreover, our findings indicate that the privacy tools supported by SNSs were insufficient to meet their privacy needs. Therefore, users in our sample have implemented a couple of self-censorship strategies which are considered dynamic and comprehensive to reach a satisfactory level of online privacy. In addition, users’ trust perceptions regarding SNSs were found to be a strong predictor of their engagement in such platform. This research enhances the existing privacy literature by providing deeper insights into the conceptualization of users’ privacy-related decisions in SNSs and understanding how culture influences users’ privacy practices. Ultimately, such insights contribute to the development of more tailored systems that align with users' specific privacy requirements and expectations.