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Cyberbullying Score Classification Using Machine Learning Techniques

Sharma, Kunal (2017) Cyberbullying Score Classification Using Machine Learning Techniques. Masters thesis, Dublin, National College of Ireland.

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Abstract

The number of users on social networking sites are increasing day by day. The advent of technology in social space is also opening the gates of user vulnerability. On social networking sites people can show love, affection, likes, and on the other hand people can be rude, disrespectful, and violent. There have been many incidents of cyberbullying and cyberaggression reported in the online space. The incidents cant be stopped but can be controlled if awareness and restrictions are placed before entering the online social space. As part of the thesis project, the dataset of Instagram posts has been requested and collected from University of Boulder, Colorado. The dataset has 2219 observation with metadata as id, likes, follows, followed by, shared media, cyberaggression vote score, and 195 comments per Instagramers ID. The target variable is the cyberbullying vote score which ranges from 0 (no/zero votes to bullying) to 5 (5 votes to cyberbullying). The research focuses on three aspects: text mining of foul words from the comments, implementation of text classification models, and comparison of the different classifiers on the basis of the performance measure.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: CAOIMHE NI MHAICIN
Date Deposited: 28 Aug 2018 12:00
Last Modified: 28 Aug 2018 12:00
URI: http://trap.ncirl.ie/id/eprint/3088

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