Hate Speech and Offensive Content Identification in English and Bangla
Call for Participation
Task 1: Binary Classification in English.
A task focused on hate speech and offensive language identification is offered for Hinglish. It is a coarse-grained binary classification in which participants are required to classify tweets into two classes, namely: hate and offensive (HOF) and non- hate and offensive (NOT).
(NOT) Non Hate-Offensive - This post does not contain any Hate speech, profane, offensive content. (HOF) Hate and Offensive - This post contains Hate, offensive, and profane content.
(HOF) Hate and Offensive - This post contains Hate, offensive, and profane content.
Dataset
Note: Datasets are password protected, please register to get access to passwords, once register you'll receive passwords from noreply.hasoc@gmail.com, in case if you have not received passwords after registration please check your spam, please reachout to us via hasocfire@googlegroups.com in case if any queries
Results
Important Dates
Timeline:
All subtracks have an independent timeline for training/test data release and run submission which will be available on respective websites. Here are the common timelines:
20th june
Training data release
August
Results announcement
September
Working notes and overview papers due
December
FIRE conference takes place online
NOTE: All dates are in AoE timezone
Organisers
Acknowledgement
We would like to thank the AI Journal - Funding Opportunities for Promoting AI Research for supporting HASOC Task 1
Contact us
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For any queries write to us at hasoc@googlegroups.com