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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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4 results for “cyberbullying”

Generalisation of Cyberbullying Detectioncs.CL

Study explores cyberbullying datasets and classifier generalization.

problem Cyberbullying detection across different online communities.

method Analysis of various cyberbullying datasets and classifier generalization.

result Insight into classifier generalization power and interaction.

cyberbullying classifier generalization ensemble models online communities

2020-09-01abs ↗pdf ↗

HMS-BERT: Hybrid Multi-Task Self-Training for Multilingual and Multi-Label Cyberbullying Detectioncs.CL

HMS-BERT detects cyberbullying in multiple languages and labels.

problem Multilingual and multi-label cyberbullying detection challenges.

method Hybrid multi-task self-training framework using BERT.

result Strong performance on multi-label and main classification tasks.

cyberbullying multilingual multi-label BERT self-training

2026-03-13abs ↗pdf ↗

Cyberbullying Identification Using Participant-Vocabulary Consistencycs.SI

With the rise of social media, people can now form relationships and communities easily regardless of location, race, ethnicity, or gender. However, the power of social media simultaneously enables harmful online behavior such as harassment and bullying. Cyberbullying is a serious social problem, making it an important…

2016-06-26abs ↗pdf ↗

Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Networkcs.CL

Paper benchmarks Bengali language classification tasks using MConv-LSTM network.

problem Lack of computational resources for NLP tasks in under-resourced languages like Bengali.

method Built three datasets, BengFastText word embeddings, and MConv-LSTM network for hate speech detection, document classification, and sentiment analysis.

result BengFastText yields up to 92.30%, 82.25%, and 90.45% F1-scores in document classification, sentiment analysis, and hate speech detection respectively.

Bengali Multichannel Convolutional-LSTM Hate Speech Sentiment Analysis Document Classification

2020-04-11abs ↗pdf ↗