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Artificial intelligence (AI) significantly transforms social media platforms by providing exceptional personalisation and user interaction, as well as presenting important ethical dilemmas. This paper analyses various AI methodologies, encompassing machine learning, natural language processing, and reinforcement learning that underpin recommendation systems and social network analysis. It emphasises the advantages, including enhanced user pleasure and augmented revenue, as well as the hazards of data privacy violations, algorithmic bias, and manipulation. Critical concerns such as transparency, accountability, and international regulatory frameworks are examined to offer a comprehensive picture. The research additionally investigates prospective avenues, highlighting innovative technology, addressing misinformation, and enhancing public awareness. This study seeks to facilitate sustainable and ethical progress in AI-driven social media systems by addressing these elements.

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Recommendations to Manipulations: Critical Review of AI in Social Media Systems

  • 会议论文

  • 发表日期：

    2026年

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  • Utkarsha Wanjari,
  • Shubham Kishor Kadam,
  • Chhitij Raj,
  • Pankajkumar Anawade,
  • Deepak Sharma

摘要

Artificial intelligence (AI) significantly transforms social media platforms by providing exceptional personalisation and user interaction, as well as presenting important ethical dilemmas. This paper analyses various AI methodologies, encompassing machine learning, natural language processing, and reinforcement learning that underpin recommendation systems and social network analysis. It emphasises the advantages, including enhanced user pleasure and augmented revenue, as well as the hazards of data privacy violations, algorithmic bias, and manipulation. Critical concerns such as transparency, accountability, and international regulatory frameworks are examined to offer a comprehensive picture. The research additionally investigates prospective avenues, highlighting innovative technology, addressing misinformation, and enhancing public awareness. This study seeks to facilitate sustainable and ethical progress in AI-driven social media systems by addressing these elements.