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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.
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, cyberbullyingOCoethese terms, which were almost
unknown 10 years agoOCoeare 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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