Predicting the Level of Safety Feeling of Bangladeshi Internet users using Data Mining and Machine Learning

An amazing combination of cutting-edge data mining and machine learning methodologies to predict the level of safety feeling among Bangladeshi internet users, which is a significant departure in this subject. By leveraging cutting-edge algorithms and innovative data sources, this work provides previ...

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Bibliographic Details
Published in:International journal of advanced computer science & applications Vol. 14; no. 9
Main Authors: Alam, Md. Safiul, Roy, Anirban, Majumder, Partha Protim, Khushbu, Sharun Akter
Format: Journal Article
Language:English
Published: West Yorkshire Science and Information (SAI) Organization Limited 2023
Subjects:
Algorithms
Artificial intelligence
Bullying
Computer science
Cybersecurity
Data mining
Internet
Internet access
Internet service providers
Machine learning
Safety
Virtual communities
ISSN:2158-107X, 2156-5570
Online Access:Get full text
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Summary:An amazing combination of cutting-edge data mining and machine learning methodologies to predict the level of safety feeling among Bangladeshi internet users, which is a significant departure in this subject. By leveraging cutting-edge algorithms and innovative data sources, this work provides previously unheard-of insights into how this demographic perceives online safety, shedding light on an essential yet underappreciated aspect of their digital lives. This exceptional study's original research increases the body of knowledge of online safety and sets the road for policy recommendations and intervention tactics that will enable Bangladesh to become a global leader in internet security.
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ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2023.0140976