School of Engineering 300597 Master Project 1 Sydney City Session 2 2020 Edition: Sydney City Session 2 2020 Copyright ©2020 University Western Sydney trading as Western Sydney University ABN...

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· Deep learning for prediction systems such as fake news,hate speech and cyberbullying




School of Engineering 300597 Master Project 1 Sydney City Session 2 2020 Edition: Sydney City Session 2 2020 Copyright ©2020 University Western Sydney trading as Western Sydney University ABN 53 014 069 881 CRICOS Provider No: 00917K No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without the prior written permission from the Dean of the School. Copyright for acknowledged materials reproduced herein is retained by the copyright holder. All readings in this publication are copied under licence in accordance with Part VB of the Copyright Act 1968. Unit Details Unit Code: 300597 Unit Name: Master Project 1 Credit Points: 10 Unit Level: 7 Assumed Knowledge: (1) Knowledge in one of the fields in engineering, construction, information technology, data science or a related discipline; (2) Knowledge in research methodology; and (3) Skills in literature review. Note: Students with any problems, concerns or doubts should discuss those with the Unit Coordinator as early as they can. Unit Convenor (SCC) Name: Dr Mahsa Razavi Email: [email protected] Consultation Arrangement: Please liaise directly with the academic teaching this unit regarding appropriate consultation times. It is usually best to make contact with these staff via email. Program Convenor (SCC) Name: Dr Mahsa Razavi Email: [email protected] Consultation Arrangement: Please liaise directly with the academic teaching this unit regarding appropriate consultation times. It is usually best to make contact with these staff via email. Note: The relevant Learning Guide Companion supplements this document Contents 1 About Master Project 1 2 1.1 An Introduction to this Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 What is Expected of You . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Changes to Unit as a Result of Past Student Feedback . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Assessment Information 4 2.1 Unit Learning Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Approach to Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Contribution to Course Learning Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.4 Assessment Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.5 Assessment Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.5.1 Supervision agreement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.5.2 Project Proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.5.3 Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.6 General Submission Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3 Teaching and Learning Activities 16 4 Learning Resources 18 4.1 Recommended Readings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 1 1 About Master Project 1 1.1 An Introduction to this Unit This unit is a problem-based project unit. Students are expected to conduct self-studies under supervision by academic staff. Students will identify research topics in consultation with supervisors, carry out literature survey in one of the fields of engineering, construction, information technology or data science. Students will be required to define research objectives and scope, establish research methodology and prepare a research plan. 1.2 What is Expected of You Study Load A student is expected to study an hour per credit point a week. For example a 10 credit point unit would require 10 hours of study per week. This time includes the time spent within classes during lectures, tutorials or practicals. Attendance It is strongly recommended that students attend all scheduled learning activities to support their learning. Online Learning Requirements Unit materials will be made available on the unit’s vUWS (E-Learning) site (https://vuws.westernsydney.edu.au/). You are expected to consult vUWS at least twice a week, as all unit announcements will be made via vUWS. Teaching and learning materials will be regularly updated and posted online by the teaching team. Special Requirements Essential Equipment: Not Applicable Legislative Pre-Requisites: Not Applicable Policies Related to Teaching and Learning The University has a number of policies that relate to teaching and learning. Important policies affecting students include: – Assessment Policy – Bullying Prevention Policy and – Guidelines – Enrolment Policy – Examinations Policy – Review of Grade Policy – Sexual Harassment Prevention Policy – Special Consideration Policy – Student Misconduct Rule – Teaching and Learning - Fundamental Code – Student Code of Conduct Academic Integrity and Student Misconduct Rule In submitting assessments, it is essential that you are familiar with the policies listed above and that you understand 2 https://vuws.westernsydney.edu.au/ https://policies.westernsydney.edu.au/document/view.current.php?id=227 https://policies.westernsydney.edu.au/document/view.current.php?id=99 https://policies.westernsydney.edu.au/document/view.current.php?id=240 https://policies.westernsydney.edu.au/document/view.current.php?id=19 https://policies.westernsydney.edu.au/document/view.current.php?id=204 https://policies.westernsydney.edu.au/document/view.current.php?id=203 https://policies.westernsydney.edu.au/document/view.current.php?id=103 https://policies.westernsydney.edu.au/document/view.current.php?id=205 https://policies.westernsydney.edu.au/document/view.current.php?id=304 https://policies.westernsydney.edu.au/document/view.current.php?id=139 https://policies.westernsydney.edu.au/view.current.php?id=00258 the principles of academic integrity. You are expected to act honestly and ethically in the production of all academic work and assessment tasks, submit work that is your own and acknowledge any contribution to your work made by others. Important information about academic integrity, including advice to students is available at https://www.westernsydney. edu.au/studysmart/home/academic_integrity_and_plagiarism. It is your responsibility to familiarise yourself with these principles and apply them to all work submitted to the University as your own. When you submit an assignment or product, you will declare that no part has been: copied from any other stu- dent’s work or from any other source except where due acknowledgement is made in the assignment; submitted by you in another (previous or current) assessment, except where appropriately referenced, and with prior permission from the Unit Coordinator; written/produced for you by any other person except where collaboration has been au- thorised by the Unit Coordinator. The Student Misconduct Rule applies to all students of Western Sydney University and makes it an offence for any student to engage in academic, research or general
Answered Same DayAug 03, 2021

Answer To: School of Engineering 300597 Master Project 1 Sydney City Session 2 2020 Edition: Sydney City...

Abhishek answered on Aug 06 2021
149 Votes
DEEP LEARNING FOR PREDICTION SYSTEMS SUCH AS FAKE NEWS, HATE SPEECH AND CYBERBULLYING
(RESEARCH PROPOSAL)
Abstract
The purpose of this research proposal is to provide the details of the several aspects related to the topic. The research will be done on all the given factors. The determination of the objectives, along with the research questions, acts as a pathway for the completion of the research proposal. The literature review presented in this research will give enough substance for the proper un
derstanding of the keywords and its relevance. The well-defined research methodology is being provided that will act as guidance for the entire research. The typical aspect of cyberbullying and its types, the different kinds of laws against hate speech, is stated in the proposal. The contribution of the Artificial Intelligence (AI) in the detection of fake news is also stated in this proposal. The relevance of using different approaches to complete the task is also provided in this research proposal.
Table of Contents
Abstract    2
1: Introduction    4
1.1 Background of the Research    4
1.2 Research Rationale    4
1.3 Research Aims and Objectives    4
1.4 Research Questions    4
1.5 Research Significance    5
2: Literature Review    6
2.1 Concept of Deep Learning    6
2.2 Concept of Prediction System in Deep Learning    6
2.3 Hate Speech    6
2.4 Cyber Bullying    7
2.5 Fake News    7
3: Research Methodology    9
3.1 Research Approach    9
3.2 Research Philosophy    9
3.3 Research Design    9
3.4 Inclusion and Exclusion Criteria    9
3.5 Data Collection and Analysis Strategies    10
3.6 Timeline    10
References    11
Appendix    12
1: Introduction
1.1 Background of the Research
Cyberbullying, trolling, hate comments and fake news is some of the critical concerns of society. According to the digital world, more than 27% of the youth are affected and harassed because of the rise in cyberbullying and telling. The use of the internet has created several damages to the minds of the child. More than 13% of the children have been found under clinical depression due to the ill effects of cybercrimes (Olweus & Limber, 2018). The false information circulated the internet is the result of various drastic changes undertaken by the youth. Therefore, the research study aims to provide specific technological solutions to bring a decisive move against the ill effects of cyberbullying.
1.2 Research Rationale
The excessive increase of cyberbullying, hate comments, trolls and fake news is the research issue. The research addresses how the concepts of deep learning can help in mitigating the ill effects of the internet over society. It is an issue because of the excessive use of the internet has created a clinical depression among the youth of society.
It is an issue because the misuse of the internet is affecting the lives of the people in a very negative way. It is an issue now because this is the age of technology. Every individual is using social media platforms. Social media platforms have become the central point to reveal someone’s opinions. These negative opinions are creating bad influence over others. The research sheds light on the necessity of deep learning to restrict the misuse of the internet. The study provides a new dimension towards discovering ways to limit the negative impacts of the internet.
1.3 Research Aims and Objectives
· To understand the concepts of Deep learning
· To understand the effectiveness of deep learning on restricting the issue of the internet
· To evaluate the various impacts that use of the internet has on the youth
· To understand how deep learning can be implemented in the provision of hate speech and trolling
· To evaluate how deep earning can bring out a positive impact on the mindsets of the trollers and the misusers of the internet
1.4 Research Questions
· What are the concepts of deep learning?
· How can in-depth learning help in restricting the misuse of the internet?
· How can deep learning have a positive impact on the minds of the users of the internet?
1.5 Research Significance
The research is highly significant because it tries to find solutions to cyberbullying, fake news and other ill effects of the internet. The study is essential as it can prove to be a pathfinder towards the narrow and conservative world of the internet. Through this research, the effectiveness of technological advancements would be understood. It shows how Deep Learning can be utilised to restrict the ill growth of misuse of the internet (Englander et al. 2018). The research is significant, as it would help in bringing a new dimension in the protection of legal privacy. The study would help in restricting the misuse of the internet.
2: Literature Review
2.1 Concept of Deep Learning
Deep learning is a branch of artificial intelligence that is designed to imitate the human brain and its working capabilities. It is the methods, in which the processing of the data is possible to detect the objects, to recognise the speech and in the translation of the languages. Deep learning is created and...
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