1st CFP: (HASOC-meme ) Hate Speech and Offensive Content Identification in Memes in Bengali, Hindi, Gujarati and Bodo: FIRE 2025 track
Koyel Ghosh
[Apologies for multiple postings]
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[CFP] HASOC-meme: Hate Speech and Offensive Content Identification in Memes in Bengali, Hindi, Gujarati and Bodo at FIRE 2025 ************************************************************************************
We are excited to announce the 7th edition of HASOC, featuring a range of engaging shared tasks. We warmly invite you to participate in this edition. HASOC 2025 will introduce classification tasks on memes, focusing on the identification of abuse, sentiment, sarcasm, vulgarity, and target. The task will primarily include three binary classification tasks, one multi-class classification task, and one multi-label classification task on memes in Bangla, Hindi, Gujarati, and Bodo languages.
Track Description: This task involves analyzing multimodal data (image and text) to detect abuse, identify targeted communities, assess vulgarity and sarcasm, and assign sentiment labels. So, the task will be in five parts.
Sentiment detection:
• Positive - The meme conveys a supportive, humorous, or appreciative tone.
• Neutral - The meme is neither overtly positive nor negative in tone.
• Negative - The meme expresses hostility, mockery, or criticism.
Sarcasm Detection:
• Sarcastic - The meme presents statements or visuals that imply the opposite of their literal meaning, often to mock or ridicule.
• Non-Sarcastic: The meme directly conveys its message without sarcasm or irony.
Vulgarity Detection:
• Vulgar - The meme contains explicit or offensive words, gestures, or depictions.
• Not Vulgar - The meme does not include any such content.
Abuse Detection:
• Abusive - The meme includes offensive, harmful, or derogatory language, imagery, or implications targeting an individual or a group.
• Non-abusive - The meme does not contain any offensive, harmful, or derogatory content.
Target Community Identification:
• Gender - Any reference to male, female, non-binary, or transgender identities.
• Religion - Mentions or imagery related to any religious belief, deity, or practice.
• Individual - Specifically mentions or portrays a particular person.
• Political - Targets political ideologies, parties, politicians, or policies.
• National Origin - Targets people based on their country or ethnicity.
• Social Sub-groups - Groups based on socio-economic status, occupation, cultural identity, or other affiliations.
• Others - Any target that does not fall into the above categories.
• None - If the meme does not target any specific community, no target label is assigned.
Important dates
Registration starts: 15th May, 2025
Hindi, Marathi and Bodo Training Data Release: 17th May, 2025
Bangla Training data release: 24th May, 2025
Release of the test set: 15th June, 2025
Run submission deadline: 30th June, 2025
Announcement of results: 15 July, 2025
Working notes due: 30th August, 2025
Camera-ready copies of notes and overview paper: 30th September, 2025
Website: https://hasocfire.github.io/hasoc/2025/call_for_participation.html
Koyel Ghosh
Task organizers
Prof. Dr. Thomas Mandl :- University of Hildesheim, Germany
Prof. Dr. Utpal Garain :-Indian Statistical Institute, India
Prof. Dr. Debasis Ganguly :- University of Glasgow, United Kingdom
Prof. Dr. Sandip Modha :- University of Milano-Bicocca, Italy & LDRP-ITR, Gandhinagar, India
Prof. Dr. Animesh Mukherjee :- Indian Institute of Technology, Khargapur, India
Dr. Koyel Ghosh :- University of Hildesheim, Germany
Dr. Mithun Das :- Indian Institute of Technology, Khargapur, India
Shubhankar Barman :- BITS pilani, India
Mwnthai Narzary :- Central Institute of Technology, Kokrajhar, India
Saptarshi Saha :- Indian Statistical Institute, Kolkata, India
Website: https://hasocfire.github.io/hasoc/2025/call_for_participation.html