Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate

Hate speech is a universal problem from time immemorial. The high adoption of social media (SM) has made it a problem of gigantic proportions during elections in Nigeria. The anonymity enjoyed by the users is the main reason for the high volume of cyber hate in Nigeria's social media space. Pol...

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Bibliographic Details
Main Author:	Sallau, Mullah Nanlir
Format:	Thesis
Language:	English
Published:	2023
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/60447/1/24%20Pages%20from%20MULLAH%20NANLIR%20SALLAU.pdf
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id	my-usm-ep.60447
record_format	uketd_dc
spelling	my-usm-ep.604472024-04-29T01:38:29Z Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate 2023-04 Sallau, Mullah Nanlir QA75.5-76.95 Electronic computers. Computer science Hate speech is a universal problem from time immemorial. The high adoption of social media (SM) has made it a problem of gigantic proportions during elections in Nigeria. The anonymity enjoyed by the users is the main reason for the high volume of cyber hate in Nigeria's social media space. Politicians usually circulate different politically motivated hate messages on social media during elections. Though, different artificial intelligence (AI) approaches such as machine learning models have been developed to address the problem with reasonable success. Nonetheless, the problem persists and leads to a high rate of cyberhate crime in Nigeria. The main problem is the lack of research to build models to address peculiarities in Nigeria. These problems made existing models incapacitated in Nigeria's cyberspace. To solve the identified research gaps from the vantage point of a machine learning researcher, the problem was modelled as a text classification task. To achieve the main objective, the study proposed to enhance a technique called the stacking ensemble method. The proposed method is called the heterogeneous stacked ensemble (HSE). 2023-04 Thesis http://eprints.usm.my/60447/ http://eprints.usm.my/60447/1/24%20Pages%20from%20MULLAH%20NANLIR%20SALLAU.pdf application/pdf en public phd doctoral Perpustakaan Hamzah Sendut Pusat Pengajian Sains Komputer
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Sallau, Mullah Nanlir Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate
description	Hate speech is a universal problem from time immemorial. The high adoption of social media (SM) has made it a problem of gigantic proportions during elections in Nigeria. The anonymity enjoyed by the users is the main reason for the high volume of cyber hate in Nigeria's social media space. Politicians usually circulate different politically motivated hate messages on social media during elections. Though, different artificial intelligence (AI) approaches such as machine learning models have been developed to address the problem with reasonable success. Nonetheless, the problem persists and leads to a high rate of cyberhate crime in Nigeria. The main problem is the lack of research to build models to address peculiarities in Nigeria. These problems made existing models incapacitated in Nigeria's cyberspace. To solve the identified research gaps from the vantage point of a machine learning researcher, the problem was modelled as a text classification task. To achieve the main objective, the study proposed to enhance a technique called the stacking ensemble method. The proposed method is called the heterogeneous stacked ensemble (HSE).
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Sallau, Mullah Nanlir
author_facet	Sallau, Mullah Nanlir
author_sort	Sallau, Mullah Nanlir
title	Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate
title_short	Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate
title_full	Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate
title_fullStr	Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate
title_full_unstemmed	Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate
title_sort	enhanced heterogeneous stacked ensemble machine learning model for detecting nigerian politically motivated cyberhate
granting_institution	Perpustakaan Hamzah Sendut
granting_department	Pusat Pengajian Sains Komputer
publishDate	2023
url	http://eprints.usm.my/60447/1/24%20Pages%20from%20MULLAH%20NANLIR%20SALLAU.pdf
_version_	1804888938642407424

Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate

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