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Autor(en): 
  • Michal E. Ptaszynski
  • Fumito Masui
  • Automatic Cyberbullying Detection: Emerging Research and Opportunities 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Oktober 2018  
    Genre:  Ratgeber 
    ISBN:  9781522552499 
    EAN-Code: 
    9781522552499 
    Verlag:  Information Science Reference 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 260 mm / B 183 mm / D 15 mm 
    Gewicht:  583 gr 
    Seiten:  200 
    Zus. Info:  HC gerader Rücken kaschiert 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Due to the prevalence of social network service and social media, the problem of cyberbullying has risen to the forefront as a major social issue over the last decade. Internet hate, harassment, cyberstalking, cyberbullying-these terms, which were almost unknown 10 years ago-are in the everyday lexicon of all internet users. Unfortunately, it is becoming increasingly difficult to undertake continuous surveillance of websites as new ones are appearing daily. Methods for automatic detection and mitigation for online bullying have become necessary in order to protect the online user experience. Automatic Cyberbullying Detection: Emerging Research and Opportunities provides innovative insights into online bullying and methods of early identification, mitigation, and prevention of harassing speech and activity. Explanations and reasoning for each of these applied methods are provided as well as their pros and cons when applied to the language of online bullying. Also included are some generalizations of cyberbullying as a phenomenon and how to approach the problem from a practical technology-backed point of view. The content within this publication represents the work of deep learning, language modeling, and web mining. It is designed for academicians, social media moderators, IT consultants, programmers, education administrators, researchers, and professionals and covers topics centered on identification methods and mitigation of internet hate and online harassment.

      
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