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securing social media user data -- 2

Publishing social media data would raise more concerns on user privacy. To encourage data sharing and mitigate user privacy concerns, a number of anonymization and de-anonymization algorithms have been developed to help protect privacy of social media users. In this work, we propose a new adversarial attack specialized for social media data. We further

provide a principled way to assess effectiveness of anonymizing different aspects of social media data. Our work sheds light on new privacy risks in social media data due to innate heterogeneity of user-generated data which require striking balance between sharing user data and protecting user privacy.

Skills: Python, Report Writing, Machine Learning (ML), Natural Language, Data Science

About the Client:
( 0 reviews ) Turkey, Turkey

Project ID: #34017480

11 freelancers are bidding on average $100 for this job

saminakiran2

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$100 USD in 1 day
(441 Reviews)
8.1
crispwriter

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7.2
CRBW

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6.8
maaria1991

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6.1
sajjadtaghvaeifr

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(28 Reviews)
5.9
hayteekeys

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5.2
InoovativeThink

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4.0
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3.6
writingvector

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(9 Reviews)
2.8
mandionisio154

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(1 Review)
1.5
qualityxenter

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$160 USD in 1 day
(0 Reviews)
0.0