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Hiding opinions from machine learning.

Marcin Waniek1, Walid Magdy2, Talal Rahwan1

  • 1Computer Science, New York University Abu Dhabi, Abu Dhabi 129188, United Arab Emirates.

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Summary
This summary is machine-generated.

Machine learning infers Twitter user opinions, posing privacy risks. An AI-driven approach can help users hide their opinions by modifying their online profiles.

Keywords:
Stance detectionmachine learningprivacysocial media

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Area of Science:

  • Social computing
  • Artificial intelligence
  • Human-computer interaction

Background:

  • Machine learning and big data enable detailed analysis of online activities.
  • Inference of private information and user opinions from online profiles is a growing concern.
  • Twitter users are increasingly scrutinized for their opinions on various topics.

Purpose of the Study:

  • To investigate the privacy threat posed by algorithms inferring Twitter user opinions.
  • To explore methods for users to conceal their opinions from such algorithms.
  • To develop AI-driven countermeasures for preserving user privacy.

Main Methods:

  • Survey conducted to assess user awareness and desire for opinion privacy on Twitter.
  • Analysis of user inability to identify opinion-revealing online activities.
  • Development and testing of a heuristic-based AI assistant to guide profile modifications.

Main Results:

  • Significant proportion of Twitter users wish to hide opinions on social, political, and religious issues.
  • Users struggle to identify which online activities reveal their opinions.
  • Proposed AI heuristic effectively helps users hide their opinions by suggesting profile modifications.

Conclusions:

  • Machine learning analysis of online profiles presents significant privacy risks.
  • AI-driven strategies can empower users to protect their opinion privacy.
  • Developing countermeasures is crucial for safeguarding the right to control shared personal information.