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PrivacyAlert: a dataset for image privacy prediction

Authors: Chenye Zhao; Caragea, Cornelia; Squicciarini, Anna Cinzia; Mangat, Jasmine; Sujay Koujalgi;

PrivacyAlert: a dataset for image privacy prediction

Abstract

This is a dataset for image privacy prediction. Images are from Flickr and annotated as private/public by crowd-sourcing platforms. Private images are ones that contain sensitive information and cannot be shared with everyone on social networking sites. Public images are ones that are safe to be shared with everyone. Our dataset can be used to train machine learning/deep learning models as binary classifiers to predict whether images contain sensitive information. Please cite: @inproceedings{zhao2022privacyalert, title={PrivacyAlert: A Dataset for Image Privacy Prediction}, author={Zhao, Chenye and Mangat, Jasmine and Koujalgi, Sujay and Squicciarini, Anna and Caragea, Cornelia}, booktitle={Proceedings of the International AAAI Conference on Web and Social Media}, volume={16}, pages={1352--1361}, year={2022} }

Keywords

image privacy prediction

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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