Wormhole Whispers: Reflecting User Privacy Data Boundaries Through Algorithm Visualization - Xiaoxiao Wang; Jingjing Zhang; Huize Wan; Yuan Yao (Applied Sciences)
As user interactions on online social platforms increase, so does the public’s concern over the exposure of user privacy data. However, ordinary users often lack a clear and intuitive understanding of how their personal online information flows and how algorithms are involved in this process. We have developed a design to address this issue that visualizes data algorithms and transmission based on data collection and analysis. The primary contribution of this work is an innovative approach that uses metaphorical visual language to represent the flow of user data, algorithms, and information. It also aims to present these concepts interactively, allowing users to gain a more vivid understanding of the dynamic changes in their personal data. This participatory and interactive design seeks to provide users, as well as various stakeholders, an opportunity to reflect on the relationship between online society, privacy data boundaries, and users’ rights to be informed.