• شماره ركورد
    14315
  • عنوان
    تشخيص شايعهاز روي متن با استفاده از يادگيري عميق
  • سال تحصيل
    1402
  • استاد راهنما
    دكتر محمد رضا كنگاوري
  • چکيده
    Social media platforms like Facebook, Twitter, and Instagram have transformed communication but also amplified the spread of misinformation, leading to significant damage to businesses, governments, and individuals. Traditional fact-checking methods struggle to keep up with the speed and volume of content online, but machine learning and deep learning techniques, such as CNNs and LSTMs, offer hope in detecting misinformation more effectively. However, these methods face challenges in understanding the global dynamics of falsehoods' spread, necessitating further research and innovation to combat this growing problem. To improve rumor detection using deep learning, several key strategies are recommended. First, it's crucial to develop models that capture both local and global context in information propagation, incorporating user behavior analysis and network-based features. Second, integrating multimodal data, such as text with images, videos, and user interactions, can enhance detection accuracy. Third, employing ensemble methods that combine the strengths of various deep learning architectures may improve robustness against evolving misinformation tactics. Lastly, continuous training and updating of models with real-time data are essential to keeping up with the rapidly changing nature of social media content. The spread of misinformation is not a new problem, but it has become increasingly complex and challenging to address in the digital age. Traditional methods of debunking rumors, such as manual fact-checking, are insufficient against the rapid spread of misinformation online. Machine learning and deep learning techniques offer promising solutions, but they need to account for the complex dynamics of information spread on social media to be truly effective. Ongoing research and innovation are required to develop tools that can detect and counteract misinformation before it causes significant harm.
  • نام دانشجو

    اسراء داود

  • تاريخ ارائه
    12/11/2024 12:00:00 AM
  • متن كامل
    85273
  • پديد آورنده

    اسرا داود

  • تاريخ ورود اطلاعات
    1403/10/01
  • عنوان به انگليسي
    Rumor Detection from Text using Deep Learning
  • كليدواژه هاي فارسي
    ياد گيري عمق , متن كاوي , تشخيص شايعه , تايم اصلي , مديريت واقعي داده ها
  • كليدواژه هاي لاتين
    real time , data handeling , Rumor Detection, , Text mining , , and Deep Learning