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Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset

Nowadays, the online platform is primarily used to communicate and connect with people. It controlled many lives based on many aspects. When online, not all users prefer what they see. They can speak up without thinking about the effect on someone. From this event, it may lead to cyberbullying activ...

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Main Author: Afiefah Hannani, Abdul Halim
Format: Undergraduates Project Papers
Language:English
Published: 2023
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/40196/1/CA19084.pdf
http://umpir.ump.edu.my/id/eprint/40196/
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spelling my.ump.umpir.401962024-02-07T04:19:52Z http://umpir.ump.edu.my/id/eprint/40196/ Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset Afiefah Hannani, Abdul Halim QA75 Electronic computers. Computer science Nowadays, the online platform is primarily used to communicate and connect with people. It controlled many lives based on many aspects. When online, not all users prefer what they see. They can speak up without thinking about the effect on someone. From this event, it may lead to cyberbullying activity since all the users are free to throw their opinion on social media without hesitation. Not only that, but based on online judgment, it can also affect someone’s mental health. Therefore, cyberbullying detection using a Machine Learning approach is suggested. This study presents the comparison of three Machine Learning algorithms for the detection using cyberbullying activity on social media platforms specifically Twitter. The dataset to perform the algorithm will be retrieved from an open-source website called Kaggle where it will be used for the training and testing process. The algorithms include Support Vector Machine (SVM), Naïve Bayes, and Decision Tree. The purpose of this study is to see the accuracy of the algorithms and compare it. The highest algorithm will be chosen as the best model and algorithm that can be used to detect cyberbullying tweet text. 2023-02 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40196/1/CA19084.pdf Afiefah Hannani, Abdul Halim (2023) Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset. Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah.
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Afiefah Hannani, Abdul Halim
Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset
description Nowadays, the online platform is primarily used to communicate and connect with people. It controlled many lives based on many aspects. When online, not all users prefer what they see. They can speak up without thinking about the effect on someone. From this event, it may lead to cyberbullying activity since all the users are free to throw their opinion on social media without hesitation. Not only that, but based on online judgment, it can also affect someone’s mental health. Therefore, cyberbullying detection using a Machine Learning approach is suggested. This study presents the comparison of three Machine Learning algorithms for the detection using cyberbullying activity on social media platforms specifically Twitter. The dataset to perform the algorithm will be retrieved from an open-source website called Kaggle where it will be used for the training and testing process. The algorithms include Support Vector Machine (SVM), Naïve Bayes, and Decision Tree. The purpose of this study is to see the accuracy of the algorithms and compare it. The highest algorithm will be chosen as the best model and algorithm that can be used to detect cyberbullying tweet text.
format Undergraduates Project Papers
author Afiefah Hannani, Abdul Halim
author_facet Afiefah Hannani, Abdul Halim
author_sort Afiefah Hannani, Abdul Halim
title Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset
title_short Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset
title_full Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset
title_fullStr Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset
title_full_unstemmed Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset
title_sort behaviour analysis among adolescents and children for cyberbullying based on twitter and kaggle dataset
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/40196/1/CA19084.pdf
http://umpir.ump.edu.my/id/eprint/40196/
_version_ 1822924125063086080
score 13.235362

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