Online Social Network Bullying Detection Using Intelligence Techniques

@article{Nandhini2015OnlineSN,
  title={Online Social Network Bullying Detection Using Intelligence Techniques},
  author={B. Sri Nandhini and J. I. Sheeba},
  journal={Procedia Computer Science},
  year={2015},
  volume={45},
  pages={485-492}
}

Taxonomy of Cyberbullying Detection and Prediction Techniques in Online Social Networks

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A broad survey of all recent techniques proposed by researchers for cyberbullying detection and prediction is done and a comparative analysis and classification of the work done in recent years is presented.

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  • 2020
TLDR
A SA model for identifying cyberbullying texts in Twitter social media is proposed and encouraging outcomes are shown when a higher n-grams language model is applied on such texts in comparison with similar previous research.

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Cyberbully Detection Using Term Weighting Scheme and Naïve Bayes Classifier

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The aim of this research is to detect the presence of text cyberbullying from online post by comparing two term weighting schemes and two classification algorithms, and shows that Naive Bayes classifier yields a better accuracy when used with TF-IDF which is 97.60%.

Automatic detection of cyberbullying in social media text

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This paper describes the collection and fine-grained annotation of a cyberbullying corpus for English and Dutch and performs a series of binary classification experiments to determine the feasibility of automatic cyberbullies detection.
...

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