# Privacy Information Classification: A Hybrid Approach

arXiv: https://arxiv.org/abs/2101.11574 · HTML: https://mlsanity.com/paper/2101.11574/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 27 Jan 2021.

## Abstract (arXiv)

A large amount of information has been published to online social networks every day. Individual privacy-related information is also possibly disclosed unconsciously by the end-users. Identifying privacy-related data and protecting the online social network users from privacy leakage turn out to be significant. Under such a motivation, this study aims to propose and develop a hybrid privacy classification approach to detect and classify privacy information from OSNs. The proposed hybrid approach employs both deep learning models and ontology-based models for privacy-related information extraction. Extensive experiments are conducted to validate the proposed hybrid approach, and the empirical results demonstrate its superiority in assisting online social network users against privacy leakage.