@inproceedings{naseem-etal-2026-semeval,
title = "{S}em{E}val-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization",
author = {Naseem, Usman and
Geislinger, Robert and
Ren, Ada and
Kohail, Sarah and
Garrido Veliz, Rudy and
Sahil, P Sam and
Zhang, Yiran and
Stranisci, Marco Antonio and
Abdulmumin, Idris and
Alacam, {\"O}zge and
Acarturk, Cengiz and
Jabr, Aisha and
Anwar, Saba and
Ayele, Abinew Ali and
Tutubalina, Elena and
Htet, Aung Kyaw and
Wang, Xintong and
Thapa, Surendrabikram and
Chakraborty, Tanmoy and
Kodati, Dheeraj and
Moradizeyveh, Sahar and
Alam, Firoj and
Kyaw Thu, Ye and
Parida, Shantipriya and
Qazi, Ihsan Ayyub and
Wanzare, Lilian Diana Awuor and
Odhiambo, Nelson and
Siro, Clemencia and
Ahmad, Ibrahim Said and
Ali, Adem Chanie and
Semmann, Martin and
Biemann, Chris and
Muhammad, Shamsuddeen Hassan and
Yimam, Seid Muhie},
editor = "Kochmar, Ekaterina and
Ghosh, Debanjan and
North, Kai and
Komachi, Mamoru",
booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.semeval-1.453/",
pages = "3779--3796",
ISBN = "979-8-89176-414-9",
abstract = "We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances. Each data instance is multi-labeled with the presence of polarization, polarization type, and polarization manifestation. Participants were asked to predict labels in three subtasks: (1) detecting the presence of polarization, (2) identifying the type of polarization, and (3) recognizing the polarization manifestation. The three tasks attracted over 1,000 participants worldwide and more than 10k submissions on Codabench. We received final submissions from 67 teams and 69 system description papers. We report the baseline results and analyze the performance of the best-performing systems, highlighting the most common approaches and the most effective methods across different subtasks and languages. The dataset and other resources for this task are publicly available."
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<abstract>We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances. Each data instance is multi-labeled with the presence of polarization, polarization type, and polarization manifestation. Participants were asked to predict labels in three subtasks: (1) detecting the presence of polarization, (2) identifying the type of polarization, and (3) recognizing the polarization manifestation. The three tasks attracted over 1,000 participants worldwide and more than 10k submissions on Codabench. We received final submissions from 67 teams and 69 system description papers. We report the baseline results and analyze the performance of the best-performing systems, highlighting the most common approaches and the most effective methods across different subtasks and languages. The dataset and other resources for this task are publicly available.</abstract>
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%0 Conference Proceedings
%T SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization
%A Naseem, Usman
%A Geislinger, Robert
%A Ren, Ada
%A Kohail, Sarah
%A Garrido Veliz, Rudy
%A Sahil, P. Sam
%A Zhang, Yiran
%A Stranisci, Marco Antonio
%A Abdulmumin, Idris
%A Alacam, Özge
%A Acarturk, Cengiz
%A Jabr, Aisha
%A Anwar, Saba
%A Ayele, Abinew Ali
%A Tutubalina, Elena
%A Htet, Aung Kyaw
%A Wang, Xintong
%A Thapa, Surendrabikram
%A Chakraborty, Tanmoy
%A Kodati, Dheeraj
%A Moradizeyveh, Sahar
%A Alam, Firoj
%A Kyaw Thu, Ye
%A Parida, Shantipriya
%A Qazi, Ihsan Ayyub
%A Wanzare, Lilian Diana Awuor
%A Odhiambo, Nelson
%A Siro, Clemencia
%A Ahmad, Ibrahim Said
%A Ali, Adem Chanie
%A Semmann, Martin
%A Biemann, Chris
%A Muhammad, Shamsuddeen Hassan
%A Yimam, Seid Muhie
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F naseem-etal-2026-semeval
%X We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances. Each data instance is multi-labeled with the presence of polarization, polarization type, and polarization manifestation. Participants were asked to predict labels in three subtasks: (1) detecting the presence of polarization, (2) identifying the type of polarization, and (3) recognizing the polarization manifestation. The three tasks attracted over 1,000 participants worldwide and more than 10k submissions on Codabench. We received final submissions from 67 teams and 69 system description papers. We report the baseline results and analyze the performance of the best-performing systems, highlighting the most common approaches and the most effective methods across different subtasks and languages. The dataset and other resources for this task are publicly available.
%U https://aclanthology.org/2026.semeval-1.453/
%P 3779-3796
Markdown (Informal)
[SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization](https://aclanthology.org/2026.semeval-1.453/) (Naseem et al., SemEval 2026)
ACL
- Usman Naseem, Robert Geislinger, Ada Ren, Sarah Kohail, Rudy Garrido Veliz, P Sam Sahil, Yiran Zhang, Marco Antonio Stranisci, Idris Abdulmumin, Özge Alacam, Cengiz Acarturk, Aisha Jabr, Saba Anwar, Abinew Ali Ayele, Elena Tutubalina, Aung Kyaw Htet, Xintong Wang, Surendrabikram Thapa, Tanmoy Chakraborty, Dheeraj Kodati, Sahar Moradizeyveh, Firoj Alam, Ye Kyaw Thu, Shantipriya Parida, Ihsan Ayyub Qazi, Lilian Diana Awuor Wanzare, Nelson Odhiambo, Clemencia Siro, Ibrahim Said Ahmad, Adem Chanie Ali, Martin Semmann, Chris Biemann, Shamsuddeen Hassan Muhammad, and Seid Muhie Yimam. 2026. SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 3779–3796, San Diego, California, USA. Association for Computational Linguistics.