Inevitable Exposure: Analysing the Privacy Paradox in the Age of Digital Connectivity with Machine Learning Paradigms

Cheung, Ming; Ng, Stephanie; Zhang, James; Lim, Chee Peng

Inevitable Exposure: Analysing the Privacy Paradox in the Age of Digital Connectivity with Machine Learning Paradigms

conference contribution

posted on 2025-01-19, 22:29 authored by Ming Cheung, Stephanie Ng, James ZhangJames Zhang, Chee Peng Lim

Inevitable Exposure: Analysing the Privacy Paradox in the Age of Digital Connectivity with Machine Learning Paradigms

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DOI - Is version of https://doi.org/10.1109/prml62565.2024.10779613

Location

Chongqing, China

Open access

No

Language

Eng

Publication classification

E1 Full written paper - refereed

Volume

00

Pagination

164-169

Start date

2024-07-19

End date

2024-07-21

ISBN-13

979-8-3503-5592-5

Title of proceedings

PRML 2024 : Proceedings of the IEEE 5th International Conference on Pattern Recognition and Machine Learning 2024

Event

Pattern Recognition and Machine Learning. Conference (5th : 2024 :Chongqing, China)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Publication URL

https://doi.org/10.1109/prml62565.2024.10779613

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Keywords

Machine Learning and Artificial Intelligence privacy paradox information security social media discourse analysis natural language processing

Inevitable Exposure: Analysing the Privacy Paradox in the Age of Digital Connectivity with Machine Learning Paradigms

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Related Materials

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Open access

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