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Artificial Neural Network (ANN) plays an important role in shaping modern social media platforms. The networks assist in presenting content recommendations, analyzing user engagement, detecting sentiment, and automating moderation processes. Through the processing of user data, ANNs enhance personalization, improve advertising strategies, and detect harmful content, ensuring a seamless and engaging user experience. This paper explores the diverse applications of ANNs in social media, highlighting their impact on user interaction, content curation, and platform security. This review highlights key advancements, challenges, and open issues related to data variations, and evaluation criteria in social media analysis. Additionally, a structured framework is proposed for future studies focused on leveraging ANNs to gain social media insights.

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Artificial Neural Networks Applications in Social Media

  • 会议论文

  • 发表日期：

    2026年

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  • Kumar Rahul,
  • Ramjee Prasad Gupta,
  • Neeraj Arora,
  • Surender Kumar Kulshrestha

摘要

Artificial Neural Network (ANN) plays an important role in shaping modern social media platforms. The networks assist in presenting content recommendations, analyzing user engagement, detecting sentiment, and automating moderation processes. Through the processing of user data, ANNs enhance personalization, improve advertising strategies, and detect harmful content, ensuring a seamless and engaging user experience. This paper explores the diverse applications of ANNs in social media, highlighting their impact on user interaction, content curation, and platform security. This review highlights key advancements, challenges, and open issues related to data variations, and evaluation criteria in social media analysis. Additionally, a structured framework is proposed for future studies focused on leveraging ANNs to gain social media insights.