[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123816-en":3,"doc-seo-123816-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123816,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Enhanced Heterogeneous Stacked Ensemble Machine Learning Model for Detecting Nigerian Politically Motivated Cyberhate","The thesis develops and evaluates an enhanced heterogeneous stacked ensemble machine learning approach to detect Nigerian politically motivated cyberhate. It frames the problem through background on cyberhate and its specific dynamics in Nigeria, then reviews challenges in identification and the use of cyberhate datasets. The study outlines research aims, questions, expected contributions, and the significance and scope of the work, positioning the proposed model within hate-speech detection machine learning methods.","ENHANCED HETEROGENEOUS STACKED ENSEMBLE MACHINE LEARNING MODEL FOR DETECTING NIGERIAN POLITICALLY MOTIVATED CYBERHATE  \nMULLAH NANLIR SALLAU  \nUNIVERSITI SAINS MALAYSIA  \nENHANCED HETEROGENEOUS STACKED ENSEMBLE MACHINE LEARNING MODEL FOR DETECTING NIGERIAN POLITICALLY MOTIVATED CYBERHATE  \nby  \nMULLAH NANLIR SALLAU  \nThesis submitted in fulfilment of the requirements for the degree of  \nDoctor of Philosophy  \nACKNOWLEDGEMENT  \nMy sincere and profound gratitude goes to God almighty for His enabling grace and mercy over my life throughout this program. His presence made this dream of mine a reality. I remain grateful to God in every aspect of my life.  \nTo my wife, thank you! This is the second time God is permitting me to leave you and the children in Nigeria. I sincerely appreciate your patience and hard work to keep the family going. Thank you for your understanding and patience. To Zhanfa Nanlir and Co, thank you all!  \nTo my main supervisor, Associate Professor Dr Wan Mohd Nazmee Wan Zainon, thank you for being there for me all the time. You respond to my messages as promptly as possible, thank you. You gave me all I need to succeed in the PhD journey, thankyou. You play the roles of both the father and the supervisor to me. God will reward you greatly for your humility and patience.  \nTo the co-supervisor, Dr Mohd Nadhir Ab Wahab and the review team, I am sincerely grateful for critiquing the work right from the proposal stage to the final stage of this work. I am grateful and wish all of you God’s blessings.  \nI am thankful to the Federal College of Education Pankshin management team under the leadership of Dr. Amos Bulus Cirfat. A special thanks to my Dean, Dr Solomon Mangvwat who stood by me during the storm and trying moment. Grateful to Mr Mbwas Caleb and the entire GSE department for nominating me for the TETFund sponsorship.  \nTo the Dean, Professor Dr Bahari Belaton, thank you for your encouragement. To all staff of the School of Computer Sciences, I appreciate you all. To my former Dean, Professor Dr Rosni Abdullah, thank you. You did everything humanly possible to make us better researchers. It is worthy of emulation that even at the point of retirement you still dedicate your time to give your best to make us independent researchers. God bless and keep you in good health. Thank you.  \nTo my former supervisor at Coventry University, United Kingdom, Dr Ali Niknejad, I say thank you. The mentor-mentee relationship that started in 2015 still lasts to date. Thank you for your encouragement and financial assistance. Remain blessed!  \nDr Gwangtim T. Poyi, I sincerely appreciate the encouragement to push harder during the storm at FCEP. Architect Chris Gamde, thank you for your efforts to see that I succeed. I sincerely appreciate the efforts of Mr Sunday Gomo for his encouragement. To Dr Abrar Noor Akramin Kamarudin and Dr Haziqah Shamsudin, you people made me feel at home in Malaysia, thank you.  \nThe space is not enough to list every person’s name here. God will bless everyone who has assisted me in one way or the other during my PhD journey. Thank you!  \nTABLE OF CONTENTS  \nACKNOWLEDGEMENT......................................................................................... ii  \nTABLE OF CONTENTS ......................................................................................... iv  \nLIST OF TABLES .................................................................................................... xi  \nLIST OF FIGURES ................................................................................................ xiii  \nLIST OF ABBREVIATIONS ................................................................................. xv  \nABSTRAK ............................................................................................................. xviii  \nABSTRACT.............................................................................................................. xx  \n INTRODUCTION .....................","cbCairm24JuZLrWW","https://ap.wps.com/l/cbCairm24JuZLrWW","pdf",798885,1,46,"English","en",105,"# Acknowledgement\n# Table of Contents\n# List of Tables\n# List of Figures\n# List of Abbreviations\n# Abstract\n# Introduction\n## Motivation for Study\n## Statement of the Problem\n## Research Questions\n## Research Aim and Objectives\n## Expected Contributions from This Study\n## The Significance of the Study\n## Scope of the Study\n## Thesis Organisation\n# Literature Review\n## Overview\n## Background of Cyberhate\n## Machine Learning Methods for Hate Speech Detection","[{\"question\":\"What problem does the thesis address?\",\"answer\":\"The thesis targets the detection of Nigerian politically motivated cyberhate using machine learning, focusing on the difficulties of identifying cyberhate reliably.\"},{\"question\":\"What background topics are covered before building the model?\",\"answer\":\"It reviews cyberhate concepts, the Nigerian context, challenges in cyberhate identification, and the relevant cyberhate dataset, followed by hate-speech detection methods.\"},{\"question\":\"How is the proposed solution positioned within the research?\",\"answer\":\"The work defines research questions, aims, objectives, expected contributions, and the study’s scope, then places the enhanced heterogeneous stacked ensemble model within machine learning approaches for hate speech detection.\"}]","Enhanced Heterogeneous Stacked Ensemble Machine Learning Model for Detecting Nigerian Politically Motivated Cyberhate | 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