A systematic literature analysis of Cyberbullying Detection on Social Media using Text based Sentiment Analysis
Cyberbullying Detection, Machine Learning, Sentiment Analysis, Social Media Additional Key Words and Phrases: Lexicon dictionary, Neural Network
Compared to last few years Internet users are increasing day by day and along with the straight up line teenagers and school children also become used to with Internet like one essential part of routine. Parallelly Cyber-crimes are growing at tremendous rate like Cyberbullying, Cyberstalking, Denigration, Trickery, Outing, Flaming, Impersonation and many more. Among all Cyberbullying is one of the major challenges facing by many school students, teenagers and adolescents especially. Actually, age is no bar for this type of crimes but people are neither following any netiquettes even after knowing well nor some of them have any knowledge regarding how to use Internet and Social Media securely. Social Media has now become one vital part of people as it connects many friends and relatives together and give them freedom to post and connect from anywhere, anytime to remove their loneliness. They publicly and freely express their emotions and opinions or reviews on social media like twitter which is very popular and maximum cases of Cyberbullying occurs on this platform, which is targeted by bully and trapped them in major crimes. Sentiment Analysis is playing important role to figure out whether tweets containing positive sentiment or negative that is major goal of this paper by literature review of about 32 papers and can try to mitigate this harmful challenge due to which people face many mental, emotional and physical loss using Machine Learning algorithm.
Article Details
Unique Paper ID: 151691

Publication Volume & Issue: Volume 8, Issue 1

Page(s): 596 - 604
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