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Sentiment Informed Cyberbullying Detection in Social Media

Abstract Cyberbullying is a phenomenon which negatively affects individuals. Victims of the cyberbullying suffer from a range of mental issues, ranging from depression to low self-esteem. Due to the advent of the social media platforms, cyberbullying is becoming more and more prevalent. Traditional mechanisms to fight against cyberbullying include use of standards and guidelines, human moderators, use of blacklists based on profane words, and regular expressions to manually detect cyberbullying. However, these mechanisms fall short in social media and do not scale well. Users in social media use intentional evasive expressions like, obfuscation of abusive words, which necessitates the development of a sophisticated learning framework to automaticall... (more)
Created Date 2017
Contributor Dani, Harsh (Author) / Liu, Huan (Advisor) / Tong, Hanghang (Committee member) / He, Jingrui (Committee member) / Arizona State University (Publisher)
Subject Computer science / Cyberbullying / Sentiment / Social Media
Type Masters Thesis
Extent 52 pages
Language English
Reuse Permissions All Rights Reserved
Note Masters Thesis Computer Science 2017
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis