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IEEE Final Year Project Topic for CSE

Base Paper Title

Predicting Cyber bullying on Social Media in the Big Data Era Using Machine Learning Algorithms:Review of Literature and Open Challenges

Our Title

IEEE Project Abstract

Prior to the innovation of information communication technologies (ICT), social interactions evolved within small cultural boundaries such as geo spatial locations. The recent developments of communication technologies have considerably transcended the temporal and spatial limitations of traditional communications. These social technologies have created a revolution in user-generated information, online human networks, and rich human behavior-related data. However, the misuse of social technologies such as social media (SM) platforms, has introduced a new form of aggression and violence that occurs exclusively online. A new means of demonstrating aggressive behavior in SM websites are highlighted in this paper. The motivations for the construction of prediction models to ght aggressive behavior in SM are also outlined.We comprehensively review cyber bullying prediction models and identify the main issues related to the construction of cyber bullying prediction models in SM. This paper provides insights on the overall process for cyber bullying detection and most importantly overviews the methodology. Though data collection and feature engineering process has been elaborated, yet most of the emphasis is on feature selection algorithms and then using various machine learning algorithms for prediction of cyber bullying behaviors. Finally, the issues and challenges have been highlighted as well, which present new research directions for researchers to explore.

Existing System

Drawback of Existing System

Proposed System

Advantage of Proposed System

Enhancement from Base Paper

Architecture

Technology Used : Hardware & Software

Existing Algorithm

Proposed Algorithm

Advantages of Proposed Algorithm

Project Modules

Literature Survey

Conclusion

Future Work

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