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Viral news rapidly influences public perception, making pre-publication virality prediction invaluable for optimizing engagement. This study develops a News Retrieval system using BERT to predict article virality based solely on headlines. The model analyzes linguistic and contextual features to forecast sharing potential, improving both archiving processes and journalistic practices. By testing multiple headline options, journalists can select those most likely to achieve widespread reach, enhancing content strategy through data-driven insights.

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BERT for Viral News Retrieval and Prediction

  • 会议论文

  • 发表日期：

    2026年

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  • Harsh Singh,
  • Shubh Bharadwaj,
  • Chiraag Pokhariyal,
  • V. Mahabala Aditya Sharma,
  • Shashi Mehrotra

摘要

Viral news rapidly influences public perception, making pre-publication virality prediction invaluable for optimizing engagement. This study develops a News Retrieval system using BERT to predict article virality based solely on headlines. The model analyzes linguistic and contextual features to forecast sharing potential, improving both archiving processes and journalistic practices. By testing multiple headline options, journalists can select those most likely to achieve widespread reach, enhancing content strategy through data-driven insights.