Call for Shared Task Participation - HASOC-2022
Damith Premasiri
14th meeting of Forum for Information Retrieval Evaluation
HASOC-2022
Shared task on HATE AND OFFENSIVE CONTENT IDENTIFICATION
FIRE-22 9th to 13th Dec 2022 in a Hybrid mode at Kolkata, India
Call for Shared Task Participation
Task description:
This task aims to study the various forms of problematic content, such as
aggressiveness, hate, offensive, and abusive content in conversational dialogue
(with context) on online platforms, such as Twitter. Systems should use the
context of a conversation in order to identify problematic content.
Task 1: ICHCL contextual
binary classification (Hinglish and German)
This task focused on the binary classification (Subtask-1) of such
conversational tweets with tree-structured data into:
(NOT) Non-Hate-Offensive - This tweet, comment, or reply does not contain any
Hate speech, or profane, offensive content.
(HOF) Hate and Offensive - This tweet, comment, or reply contains Hate,
offensive, and profane content in itself or supports hate expressed in the
parent tweet.
The data set will be offered in Code Mixed Hindi English as well as in German.
Task 2: ICHCL contextual multiclass classification
Furthermore, for Hinglish (Code Mixed Hindi English), we’re introducing a
multiclass task that further divides the HOF tweets into 2 subclasses so this
task will contain 3 labels:
(SHOF) Standalone Hate - This tweet, comment, or reply contains Hate,
offensive, and profane content in itself.
(CHOF) Contextual Hate - Comment or reply is supporting the hate, offence and
profanity expressed by its parent. This includes affirming the hate with
positive sentiment and having apparent hate.
(NOT) Non-Hate-Offensive - This tweet, comment, or reply does not contain any
Hate speech, or profane, offensive content.
For more information on task-1 and 2 please visit: https://hasocfire.github.io/hasoc/2022/ichcl.html
Task 3: Offensive Language Identification in Marathi
This task aims to evaluate the hierarchical modelling of offensive language
identification in Marathi. The task has three subtasks.
Subtask-1: Offensive Language Detection
In this subtask, the goal is to discriminate between offensive and
non-offensive posts. Offensive posts include insults, threats, and posts
containing any form of untargeted profanity. Each instance is assigned one of
the following two labels:
OFF - Posts containing any form of non-acceptable language (profanity) or a
targeted offence, which can be veiled or direct.
NOT - Posts that do not contain offence or profanity.
Subtask-2: Categorisation of Offensive Language
In subtask B, the goal is to predict the type of offence. Only posts labelled
as Offensive (OFF) in subtask A are included in subtask B. The two categories
in subtask B are the following:
Targeted Insult (TIN): Posts containing an insult/threat to an individual,
group, or others.
Untargeted (UNT): Posts containing non-targeted profanity and swearing.
Subtask-3: Offense
Target Identification
Subtask C focuses on the target of offences. Only posts that are either insults
or threats (TIN) are considered in this third layer of annotation. The three
labels in subtask C are the following:
Individual (IND): Posts targeting an individual.
Group (GRP): The target of these offensive posts is a group of people
considered to a unity due to the same ethnicity, gender or sexual orientation,
political affiliation, religious belief, or other common characteristics.
Other (OTH): The target of these offensive posts does not belong to any of the
previous two categories.
Timeline:
5th June : Task Announcement, Data of HASOC 2019,20,21 Available
1st Aug : Training Data Release
1st Sept : Test Data Release and Run Submission Starts
3rd Sept : Registration Deadline
8th Sept : Deadline for run submission
10nd Sept : Result Declaration
30th Sept : Paper Submission Deadline
10th Oct : Review Distribution
20th Oct : Revised system description paper submission
9th-13 Dec : FIRE takes place in Hybrid mode
Organizers:
Thomas Mandl - University of Hildesheim, Germany
Sandip Modha - LDRP-ITR, Gandhinagar, India
Prasenjit majumder - DA-IICT, Gandhinagar, India
Shrey Satapara - Indian Institute of Technology, Hyderabad, India
Hiren Madhu - Indian Institute of Science, Banglore, India
Tharindu Ranasinghe - University of Wolverhampton, UK
Marcos Zampieri - Rochester Institute of Technology, USA
Kai North - Rochester Institute of Technology, USA
Damith Premasiri - University of Wolverhampton, UK
For more information, please visit: https://hasocfire.github.io/hasoc/2022/index.html
For participation please visit: https://hasocfire.github.io/hasoc/2022/registration.html
For any clarification please contact us at haso...@gmail.com
Looking forward to your participation