A Trustable LSTM-Autoencoder Network for Cyberbullying Detection on Social Media Using Synthetic Data Article Swipe

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Mst Shapna Akter , Hossain Shahriar , Alfredo Cuzzocrea · YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2308.09722

Social media cyberbullying has a detrimental effect on human life. As online social networking grows daily, the amount of hate speech also increases. Such terrible content can cause depression and actions related to suicide. This paper proposes a trustable LSTM-Autoencoder Network for cyberbullying detection on social media using synthetic data. We have demonstrated a cutting-edge method to address data availability difficulties by producing machine-translated data. However, several languages such as Hindi and Bangla still lack adequate investigations due to a lack of datasets. We carried out experimental identification of aggressive comments on Hindi, Bangla, and English datasets using the proposed model and traditional models, including Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BiLSTM), LSTM-Autoencoder, Word2vec, Bidirectional Encoder Representations from Transformers (BERT), and Generative Pre-trained Transformer 2 (GPT-2) models. We employed evaluation metrics such as f1-score, accuracy, precision, and recall to assess the models performance. Our proposed model outperformed all the models on all datasets, achieving the highest accuracy of 95%. Our model achieves state-of-the-art results among all the previous works on the dataset we used in this paper.

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preprint

Language

en

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http://arxiv.org/abs/2308.09722

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https://arxiv.org/pdf/2308.09722

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green

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10

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https://openalex.org/W4386080713

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https://openalex.org/W4386080713

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DOI

https://doi.org/10.48550/arxiv.2308.09722

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Title

A Trustable LSTM-Autoencoder Network for Cyberbullying Detection on Social Media Using Synthetic Data

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Type

preprint

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Language

en

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Publication year

2023

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Publication date

2023-08-15

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Authors

Mst Shapna Akter, Hossain Shahriar, Alfredo Cuzzocrea

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https://arxiv.org/abs/2308.09722

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https://arxiv.org/pdf/2308.09722

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Yes

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OA status

green

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https://arxiv.org/pdf/2308.09722

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Concepts

Autoencoder, Computer science, Social media, Transformer, Artificial intelligence, Hindi, Word2vec, Bengali, Recall, Encoder, Machine learning, Long short term memory, Deep learning, Speech recognition, F1 score, Natural language processing, Recurrent neural network, Artificial neural network, Psychology, World Wide Web, Engineering, Electrical engineering, Embedding, Cognitive psychology, Voltage, Operating system

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0

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10

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