CBAI 2022: Edited Book: Combating Cyberbullying in Digital Media with Artificial Intelligence New York, Morocco, January 30-February 2, 2023 |
Conference website | https://sites.google.com/view/cbai-book |
Submission link | https://easychair.org/conferences/?conf=ici2c2022 |
SCOPE
With the advancement of electronics and information technologies, digital media platforms and virtual space have become a significant part of human life today. People can share and exchange information and ideas globally just with a single click. Among these digital media platforms, social networks such as Facebook, YouTube, Twitter, etc., have a good standing. They represent the most used applications by the people, everywhere and for all times so far. Moreover, the traffic generated by digital media platforms represents more than half of the web traffic worldwide.
It is a fact that the use of these digital media platforms has dramatically influenced our habits on the Internet and in our daily life. As a result, we must adequately be wary of the electronic violence propagated via social networks. Indeed, cyberbullying has recently emerged as an effective form of bullying and online harassment. This phenomenon is becoming a concern worldwide. It includes many forms such as racism, terrorism, and several types of trolling. On the other hand, Machine Intelligence (MI) and overall Artificial Intelligence have shown promise to be powerful tools in various domains, such as computer vision, natural language processing (NLP), speech recognition, computational biology, and others. Motivated by these successes, researchers worldwide have recently started investigating applications of these techniques to handle Cyberbullying issues in the modern media. In this context, in recent years, many methods such as Fuzzy Logic (FL), Evolutionary Algorithms (EA), Machine Learning (ML), Artificial Neural Networks (ANN) and Deep Learning (DL) have been applied for detecting cyberbullying content generated by digital media platforms. This book examines how machine intelligence techniques can contribute to detecting and combating cyberbullying phenomenon.
The book is intended for researchers, specialists in AI and cyberbullying, teachers and it could be helpful for undergraduate and graduate students as well.
TOPICS
Cyberbullying: State-of-the-Art Survey
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Overview of Machine Learning Techniques
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Overview Deep Learning Techniques
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Overview on Cyberbullying Features Detection/Prevention
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Cyberbullying in Online Unstructured Data
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Cyberbullying sources and Social Media
Artificial Intelligence for Cyberbullying detection
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Machine Learning and Ensemble Learning Approaches
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Deep Learning Models
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Text-Mining and Sentiment Analysis Techniques
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Graph Optimization Algorithms
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Explainable Artificial Intelligence
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Cyberbullying Detection Techniques and Coronavirus Epidemic.
Cyberbullying prevention techniques
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Machine Learning and Ensemble Learning
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Deep Learning
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Text-Mining and Sentiment Analysis Techniques
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Graph Optimization Algorithms
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Explainable Artificial Intelligence
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Cyberbullying Prevention Techniques and Coronavirus Epidemic.
Feature engineering on Cyberbullying
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Linguistics, Writing Style and Sentiment Based Features
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Social-Context Based and User’ Information Based Features
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Feature Selection, Extraction, Construction and Reduction
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Feature Analysis on Cyberbullying Detection/Prevention
Solutions and frameworks in the practice
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Benchmark Dataset for Cyberbullying Detection/Prevention
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Real-World System for Cyberbullying Detection/Prevention
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BlockChain Technology on Cyberbullying
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Tracking and aggregating Online Cyberbullying
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Cyberbullying and Social Media
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New Trends on News for Cyberbullying
Submission Instructions
Authors are invited to submit their full chapter by January 15th, 2023 Manuscripts submitted for the book must be original, must not be previously published or currently under review anywhere. Submitted manuscripts should respect the standard guidelines of the CRC Press chapter format.
Manuscripts must be prepared using Latex, or Word, and according to the CRC Press requirements.
Chapter should contain between 15-25 pages.
Manuscripts that do not follow the formatting rules will be rejected without review. Prospective authors should send their manuscripts electronically through the easychair submission system as mentioned below:
https://easychair.org/conferences/?conf=cbai2022
NB: There are no submission or acceptance fees for manuscripts submitted to this book for publication. All manuscripts are accepted based on a double-blind peer review editorial process
The chapter prior to submission should be checked for plagiarism from licensed plagiarism software like Turnitin, iThenticate, etc. The similarity content should not exceed 25% (in any case either self -sourced contents or others).
The accepted contributions will be published by CRC Press, Taylor & Francis Group.
Publication
The Book will be published by CRC Press, Taylor & Francis Group Indexed by Scopus
EDITORS
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Mohamed LAHBY University Hassan II, Casablanca, Morocco
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Al-Sakib Khan Pathan United International University, Bangladesh
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Yassine Maleh Sultan Moulay Slimane University, Morocco