Fact Check: Information about user activity can be stored and combined with other data to build or improve a profile that reflects possible interests and personal aspects.

Fact Check: "Information about user activity can be stored and combined with other data to build or improve a profile that reflects possible interests and personal aspects."

What We Know

The claim that user activity can be stored and combined with other data to build or improve a profile reflecting possible interests and personal aspects is supported by a range of studies and expert analyses. For instance, a study from the University of Maryland discusses how contextual information can be used to predict user interests, emphasizing the importance of combining various data sources to enhance user profiling (source-1).

Additionally, metadata collected during online activities—such as web browsing—plays a crucial role in this process. As outlined in a chapter on metadata and tracking, user interactions such as visited web pages, time spent on those pages, and clicks are all collected to form a comprehensive profile of user behavior and preferences (source-2). This data can then be analyzed to predict interests and personal characteristics, although it does not identify individuals directly.

Moreover, the concept of profiling is further elaborated upon in various legal and technical discussions, which define profiling as the automated processing of personal data to evaluate aspects related to a natural person, including their interests and preferences (source-3, source-4).

Analysis

The evidence supporting the claim is robust and comes from credible sources. The University of Maryland study is a peer-reviewed research document that systematically assesses how contextual data can enhance user interest modeling, making it a reliable source (source-1). The chapter on metadata and tracking is also published in an academic context, providing a comprehensive overview of how user data is collected and used for profiling (source-2).

The legal definitions provided by sources discussing GDPR compliance and profiling practices (source-3, source-4) lend further credibility to the claim, as they outline the systematic approach to data collection and analysis that underpins modern profiling techniques.

However, it is important to note that while the data collected can reflect user interests and personal aspects, it does not constitute Personally Identifiable Information (PII) unless it is linked to an individual’s identity (source-2). This distinction is crucial in discussions about privacy and consent.

Conclusion

Verdict: True
The claim that information about user activity can be stored and combined with other data to build or improve a profile that reflects possible interests and personal aspects is substantiated by credible research and expert analysis. The systematic collection and analysis of metadata and contextual information are foundational to modern profiling practices, as evidenced by multiple authoritative sources.

Sources

1. PDF Predicting User Interests from Contextual Information - UMD
2. Chapter 3 - Metadata, Tracking, and the User's Experience
3. Let's sort out this profiling and consent debate once and for all.
4. What is automated individual decision-making and profiling?
5. Understand the Salesforce Consent Data Model
6. Profile Explorer in Data Cloud
7. What is considered 'profiling'? - Data Privacy Dish
8. User Data Collection: Balancing Business Needs and User Privacy