Journal article
Protecting the anonymity of online users through Bayesian data synthesis
Expert systems with applications, v 216, p119409
15 Apr 2023
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Privacy concerns emerge when online users of popular user-generated content (UGC) platforms are identified through a combination of their structured data (e.g., location and name) and textual content (e.g., word choices and writing style). To overcome this problem, we introduce a Bayesian sequential synthesis methodology for organizations to share structured data adjoined to textual content. Our proposed approach enables platforms to use a single shrinkage parameter to control the privacy level of their released UGC data. Our results show that our synthesis strategy decreases the probability of identification of a user to an acceptable threshold while maintaining much of the textual content present in the structured data. Additionally, we find that the value of sharing our protected data exceeds that of sharing the unprotected structured data and textual content separately. These findings encourage UGC platforms that wish to be known for consumer privacy to protect anonymity of their online users with synthetic data.
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Details
- Title
- Protecting the anonymity of online users through Bayesian data synthesis
- Creators
- Matthew J. Schneider - Drexel UniversityJingchen Hu - Vassar CollegeShawn Mankad - North Carolina State UniversityCameron D. Bale - Drexel University
- Publication Details
- Expert systems with applications, v 216, p119409
- Publisher
- Elsevier
- Number of pages
- 13
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000912959500001
- Scopus ID
- 2-s2.0-85144384259
- Other Identifier
- 991021852022304721
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic
- Operations Research & Management Science