1 Ted Rogers School of Management, Ryerson University , Toronto, Canada .
2 Department of Organization Engineering, Business Administration and Statistics, Universidad Politécnica de Madrid , Madrid, Spain .
Cyberpsychol Behav Soc Netw. 2018 Jul;21(7):418-428. doi: 10.1089/cyber.2017.0709.
The study contributes to the ongoing debate about the "privacy paradox" in the context of using social media. The presence of a privacy paradox is often declared if there is no relationship between users' information privacy concerns and their online self-disclosure. However, prior research has produced conflicting results. The novel contribution of this study is that we consider public and private self-disclosure separately. The data came from a cross-national survey of 1,500 Canadians. For the purposes of the study, we only examined the subset of 545 people who had at least one public account and one private account. Going beyond a single view of self-disclosure, we captured five dimensions of self-disclosure: Amount, Depth, Polarity, Accuracy, and Intent; and two aspects of privacy concerns: concerns about organizational and social threats. To examine the collected data, we used Partial Least Squares Structural Equation Modeling. Our research does not support the presence of a privacy paradox as we found a relationship between privacy concerns from organizational and social threats and most of the dimensions of self-disclosure (even if the relationship was weak). There was no difference between patterns of self-disclosure on private versus public accounts. Different privacy concerns may trigger different privacy protection responses and, thus, may interact with self-disclosure differently. Concerns about organizational threats increase awareness and accuracy while reducing amount and depth, while concerns about social threats reduce accuracy and awareness while increasing amount and depth.
本研究为社交媒体使用背景下的“隐私悖论”持续争论做出了贡献。如果用户的信息隐私问题与他们的在线自我披露之间没有关系，通常会宣布存在隐私悖论。然而，先前的研究产生了相互矛盾的结果。本研究的新颖之处在于，我们分别考虑了公开和私下的自我披露。数据来自对 1500 名加拿大人的跨国调查。出于研究目的，我们只检查了至少有一个公开账户和一个私人账户的 545 人的子集。通过超越对自我披露的单一看法，我们捕捉到了自我披露的五个维度：数量、深度、极性、准确性和意图；以及隐私问题的两个方面：组织和社会威胁的担忧。为了检验收集的数据，我们使用了偏最小二乘结构方程建模。我们的研究不支持隐私悖论的存在，因为我们发现组织和社会威胁的隐私问题与自我披露的大多数维度之间存在关系（即使这种关系很微弱）。私人账户和公共账户上的自我披露模式没有区别。不同的隐私问题可能会引发不同的隐私保护反应，因此可能会以不同的方式与自我披露相互作用。对组织威胁的担忧会提高意识和准确性，同时减少数量和深度，而对社会威胁的担忧会降低准确性和意识，同时增加数量和深度。
