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  3. Creating a More Transparent Internet
  • Cited by 1
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    • Publisher:
      Cambridge University Press
      Publication date:
      April 2022
      May 2022
      ISBN:
      9781108641104
      9781108485760
      DOI:
      https://doi.org/10.1017/9781108641104
      Dimensions:
      (228 x 152 mm)
      Weight & Pages:
      0.57kg, 290 Pages
      Dimensions:
      Weight & Pages:
      • Series:
      Studies in Natural Language Processing
      Subjects:
      Computational Linguistics, Computer Science, Artificial Intelligence and Natural Language Processing, Language and Linguistics
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    • Selected: Digital
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    Series:
    Studies in Natural Language Processing
    Subjects:
    Computational Linguistics, Computer Science, Artificial Intelligence and Natural Language Processing, Language and Linguistics
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    Book description

    On social media, new forms of communication arise rapidly, many of which are intense, dispersed, and create new communities at a global scale. Such communities can act as distinct information bubbles with their own perspective on the world, and it is difficult for people to find and monitor all these perspectives and relate the different claims made. Within this digital jungle of perspectives on truth, it is difficult to make informed decisions on important things like vaccinations, democracy, and climate change. Understanding and modeling this phenomenon in its full complexity requires an interdisciplinary approach, utilizing the ample data provided by digital communication to offer new insights and opportunities. This interdisciplinary book gives a comprehensive view on social media communication, the different forms it takes, the impact and the technology used to mine it, and defines the roadmap to a more transparent Web.

    Reviews

    'Misinformation and disinformation on the web are problems we face as a society, and this book is for anyone looking for hope for the future! Well-regarded authors in various disciplines contribute enjoyable and informed chapters on theoretical accounts of perspectives and how they work, practical methods for discovering and measuring bias, and computational procedures for identifying and fixing perspectives at web scale with consistent and reliable results.'

    Eduard Hovy - Carnegie Mellon University

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