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Journal article

Characterizing user connections in social media through user shared image

Abstract:

Billions of user images, which are shared on social media, can be widely accessible by others due to their sharing nature. Using machine-generated labels to annotate those images is a reliable for user connections discovery on social networks. The machine-generated labels are obtained from encoded vectors using up-to-date image processing and computer vision techniques, such as convolution neural network. By analyzing 2 million user-shared images from 8 online social networks, a phenomenon is...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted manuscript

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Publisher copy:
10.1109/TBDATA.2017.2762719

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Mathematical Institute; Internet Institute
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
IEEE Transactions on Big Data Journal website
Volume:
4
Issue:
4
Pages:
447 - 458
Publication date:
2017-10-13
Acceptance date:
2017-10-02
DOI:
ISSN:
2332-7790
Pubs id:
pubs:740634
URN:
uri:acf36c1b-5d7e-4ba2-be9b-c3e84504e7da
UUID:
uuid:acf36c1b-5d7e-4ba2-be9b-c3e84504e7da
Local pid:
pubs:740634

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