Detekcija žaljivega govora
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Updated
May 22, 2017 - Jupyter Notebook
Detekcija žaljivega govora
HASOC-Dravidian-CodeMix-FIRE 2021
Data and code for paper: Context-Aware Offensive Language Detection in Human-Chatbot Conversations
EACL 2021 paper (SJ_AJ@DravidianLangTech-EACL2021: Task-Adaptive Pre-Training of Multilingual BERT models for Offensive Language Identification)
UNIX login greeters which we deserve
Identifying and Categorizing Offensive Language in Social Media (Twitter).
Translated abusive language dataset (En2Ko). Including OffensEval/AbusEval, CADD, Davidson et al., Waseem&Hovy.
SemEval 2019 - Shared Task 6: Offensive speech detection in tweets with several machine learning approaches with different features and several types of BERT
Supplementary material to the RANLP 2019 paper "Offence in Dialogues: A Corpus-Based Study"
A Brazilian Portuguese Text Offensiveness Analysis System
RO-Offense: A Novel Romanian Dataset for Offensive Language in Online Comments
a novel Romanian language dataset for offensive message detection with manually annotated comment from a local Romanian news website (stiri de cluj) into five classes
API para Decteção de comentários Ofensivos
The models developed by ASU_OPTO team as part of OffenseEval20 for Arabic tasks
MAD: A Multi-task Aggression Detection Framework
🔍 Ensuring community harmony and shielding against ads and harassment with DFA-based offensive language detection. 🌐💬
HausaHate is a benchmark dataset for Hausa hate speech detection task. it was extracted from West African Facebook pages and comprises 2,000 comments annotated according to a binary class (offensive and non-offensive) and hate speech targets (race, gender and none).
This is an Machine learning model used to identify spam words in Malayalam. The dataset is basically of tweets from different accounts.
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