Comprehensive Privacy Risk Assessment in Social Networks Using User Attributes Social Graphs and Text Analysis
The paper proposes CPRS, a unified privacy risk scoring framework that combines user attribute sensitivity/visibility, social graph structure (SimRank and PageRank), and entity-level content analysis, validated on the SNAP Facebook and Koo datasets and through a 100-participant dashboard user study.- doi
- 10.1145/3720553.3746686
- isbn
- 979-8-4007-1534-1
- name
- Comprehensive Privacy Risk Assessment in Social Networks Using User Attributes Social Graphs and Text Analysis
- source
- BITS XML + PDF figure panels
- acm_url
- https://dl.acm.org/doi/10.1145/3720553.3746686
- authors
- Md Jahangir Alam, Ismail Hossain, Sai Puppala, Sajedul Talukder
- doi_url
- https://doi.org/10.1145/3720553.3746686
- license
- CC BY-NC 4.0
- summary
- The paper proposes CPRS, a unified privacy risk scoring framework that combines user attribute sensitivity/visibility, social graph structure (SimRank and PageRank), and entity-level content analysis, validated on the SNAP Facebook and Koo datasets and through a 100-participant dashboard user study.
- keywords
- Analysis, Graph-Based Privacy Risk, Privacy Risk Assessment, Privacy Scoring Framework, Social Networks, User-Generated Content
- arxiv_url
- https://arxiv.org/abs/2507.15124
- published
- 2025-09-15
- conference
- HT '25: 36th ACM Conference on Hypertext and Social Media, Chicago, IL, USA, September 15-19, 2025
- open_access
- true
- acm_html_url
- https://dl.acm.org/doi/full/10.1145/3720553.3746686
- ccs_concepts
- Security and privacy → Privacy protections; Security and privacy → Social aspects of security and privacy; Security and privacy → Social network security and privacy
- displayAuthor
- Md Jahangir Alam, Ismail Hossain, Sai Puppala, Sajedul Talukder
- proceedings_url
- https://dl.acm.org/doi/proceedings/10.1145/3720553
- displayPublishTime
- 2025-09-15
- acm_reference_format
- (empty)
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