Accurate Cyberbullying Detection and Prevention on Social Media
نویسندگان
چکیده
منابع مشابه
Sentiment Informed Cyberbullying Detection in Social Media
Cyberbullying is a phenomenon which negatively affects the individuals, the victims suffer from various mental issues, ranging from depression, loneliness, anxiety to low self-esteem. In parallel with the pervasive use of social media, cyberbullying is becoming more and more prevalent. Traditional mechanisms to fight against cyberbullying include the use of standards and guidelines, human moder...
متن کاملAutomatic Detection of Cyberbullying in Social Media Text
While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful prevention depends on the adequate detection of potentially harmful messages and the information overload on the Web requires intelligent systems to i...
متن کاملAutomatic Detection and Prevention of Cyberbullying
Abstract—The recent development of social media poses new challenges to the research community in analyzing online interactions between people. Social networking sites offer great opportunities for connecting with others, but also increase the vulnerability of young people to undesirable phenomena, such as cybervictimization. Recent research reports that on average, 20% to 40% of all teenagers ...
متن کاملTowards Suicide Prevention: Early Detection of Depression on Social Media
The statistics presented by the World Health Organization inform that 90% of the suicides can be attributed to mental illnesses in high-income countries. Besides, previous studies concluded that people with mental illnesses tend to reveal their mental condition on social media, as a way of relief. Among all these users of social media platforms, adolescents are the most frequent ones. Hence, th...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2021
ISSN: 1877-0509
DOI: 10.1016/j.procs.2021.01.207