# Wormhole Whispers: Reflecting User Privacy Data Boundaries Through Algorithm Visualization
## 3 Design Method
### Data Analysis  
Statistical data indicate that 94.33% of comments expressed concern/fear, as shown in Table 1. Privacy invasion and data security are the primary emotional concerns. The most frequent negative keywords are \"terrifying\", \"annoying\", and \"suspicious\", highlighting users' discomfort with how platforms currently define privacy boundaries. This suggests that many users believe they are being eavesdropped on and monitored by big data. These insights provide essential data and user research references for future studies on privacy data transmission and visualization design. In analyzing privacy policy data, we focused on keywords related to the collection and processing of personal data to ensure relevance, with special attention to adjectives, adverbs, and other terms indicating attitude and degree, thereby supporting subsequent classification and visualization, as shown in Figure 2. We applied the \"Classification by Disclosure Strategy\" to examine implicit strategies within these policies--such as mandatory, suggestive, or guiding approaches--to highlight their stance on user consent (e.g., \"mandatory\" or \"optional\"). Additionally, we classified data collection sources, distinguishing between internal and external origins to clarify specific data collection paths (Figure 1). We found that most platform privacy policies persuade users to accept or comply with terms by stating that certain features cannot be used otherwise, thereby obtaining user consent. Additionally, platforms consider de-identified personal data, which cannot identify individuals, as non-private user data. These data are widely used in platform algorithms and shared with multiple parties. In situations of information asymmetry, users may place excessive trust in these platforms. Furthermore, most platform privacy policies are complex in both text and concept, making them difficult to read. Some network service providers may also write privacy policies in very general terms, only briefly explaining what data will be collected and how it will be used. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reaction** & **Definition** & **Example** & **Percentage (N)** \\ \hline \multirow{3}{*}{Concern/Fear} & Describes the user expressing & \multirow{3}{*}{_Big data is terrifying. It eavesdropped_} & \multirow{3}{*}{94.33\% (599)} \\  & anxiety or concern about data & & \\  & security, privacy, or negative & & \\  & consequences of technology. & & \\ \hline \multirow{3}{*}{Frustration/Anger} & Expresses dissatisfaction or & \multirow{3}{*}{_Every time I talk to a friend, my phone_} & \multirow{3}{*}{3.78\% (24)} \\  & frustration with the system, & & \\  & perceived invasions of privacy, or & & \\  & general irritation with technology. & & \\ \hline \multirow{3}{*}{Confusion/Curiosity} & The user is unsure about what is & \multirow{3}{*}{_How does this app know I’ve been_} & \multirow{3}{*}{1.26\% (8)} \\  & happening or is asking & & \\  & for clarification. & & \\ \hline \multirow{3}{*}{Suspicion} & The user expresses doubt or & \multirow{3}{*}{_I’m afraid of using certain social media_} & \multirow{3}{*}{0.63\% (4)} \\  & suspicion, possibly related to & & \\ \cline{1-1}  & conspiracy theories or fears about & & \\ \cline{1-1}  & being monitored. & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Classify the reactions of Weibo users using the filtering term “BigData” and “eavesdropping”. Additionally, app agreements often include clauses such as \"may include third-party products and services\" and \"share necessary information with third-party vendors\", but the purposes and scope of the shared information are not clearly defined. The services provided by third parties are mostly invisible to users, so the embedded SDKs in apps may also obtain the same data access and usage permissions without the user's knowledge. Our data analysis revealed that the information shared between apps and third parties is extensive, including device identifiers, installation permissions, and even information from other apps.