Detecting cyberbullying in tweets using Machine Learning
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Updated
Sep 28, 2021 - Jupyter Notebook
Detecting cyberbullying in tweets using Machine Learning
Public Website for Kindly
A Model Training for Cyberbullying Detection by Using Youtube Comments
Discord Cyberbullying Bot
Cyber Bullying Detection Application (CBDA)
This app predicts the nature of the tweet into 6 Categories. i.e. Age, Ethnicity, Gender, Religion, Other Cyberbullying, Not Cyberbullying.
Repository for the experiments described in "Current Limitations in Cyberbullying Detection: on Evaluation Criteria, Reproducibility, and Data Scarcity" submitted as pre-print to arXiv.
Source code and models for the paper "Cyberbullying Detection with Fairness Constraints". IEEE Internet Computing, 2020
Repository hosting dataset for the Shared Task on Aggression Identification during First Workshop on Trolling, Aggression and Cyberbullying (TRAC - 1) as COLING - 2018. Please visit the workshop website - https://sites.google.com/view/trac1/home - for more details
Cyberbullying detection using BLSTM and GloVe
CyberGuard: Machine Learning Vigilance Against Online Harassment
Project for text analytics exam - UniPi
TITAN: Text-based InTerpreter for Anti-cyberbullying using Neural networks
Identifying trolling, aggression, cyber-bullying and hate speech etc. Three classes: Overtly Aggressive (OAG), Covertly Aggressive (CAG), and Non-aggressive (NAG)
Successfully fine-tuned a pretrained DistilBERT transformer model that can classify social media text data into one of 4 cyberbullying labels i.e. ethnicity/race, gender/sexual, religion and not cyberbullying with a remarkable accuracy of 99%.
Cyber Bullying Detection ML Model (CBD.ML)
Cyber bullying detection in Twitter using machine learning
Code and data for the paper "Politeness Stereotypes and Attack Vectors: Gender Stereotypes in Japanese and Korean Language Models" (Arxiv 2023)
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