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| Natura: | Preprint |
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2026
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| Accesso online: | https://arxiv.org/abs/2604.06817 |
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| _version_ | 1866918434525151232 |
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| author | Naseem, Usman Geislinger, Robert Ren, Juan Kohail, Sarah Veliz, Rudy Garrido Sahil, P Sam Zhang, Yiran Stranisci, Marco Antonio Abdulmumin, Idris Alaçam, Özge Acartürk, Cengiz Jabr, Aisha Anwar, Saba Ayele, Abinew Ali Tutubalina, Elena Htet, Aung Kyaw Wang, Xintong Thapa, Surendrabikram Chakraborty, Tanmoy Kodati, Dheeraj Moradizeyveh, Sahar Alam, Firoj Thu, Ye Kyaw Parida, Shantipriya Qazi, Ihsan Ayyub Wanzare, Lilian Onyango, Nelson Odhiambo Siro, Clemencia Ahmad, Ibrahim Said Ali, Adem Chanie Semmann, Martin Biemann, Chris Muhammad, Shamsuddeen Hassan Yimam, Seid Muhie |
| author_facet | Naseem, Usman Geislinger, Robert Ren, Juan Kohail, Sarah Veliz, Rudy Garrido Sahil, P Sam Zhang, Yiran Stranisci, Marco Antonio Abdulmumin, Idris Alaçam, Özge Acartürk, Cengiz Jabr, Aisha Anwar, Saba Ayele, Abinew Ali Tutubalina, Elena Htet, Aung Kyaw Wang, Xintong Thapa, Surendrabikram Chakraborty, Tanmoy Kodati, Dheeraj Moradizeyveh, Sahar Alam, Firoj Thu, Ye Kyaw Parida, Shantipriya Qazi, Ihsan Ayyub Wanzare, Lilian Onyango, Nelson Odhiambo Siro, Clemencia Ahmad, Ibrahim Said Ali, Adem Chanie Semmann, Martin Biemann, Chris Muhammad, Shamsuddeen Hassan Yimam, Seid Muhie |
| contents | 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 sub-tasks: (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 submission on Codabench. We received final submissions from 67 teams and 73 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 of this task is publicly available. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_06817 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization Naseem, Usman Geislinger, Robert Ren, Juan Kohail, Sarah Veliz, Rudy Garrido Sahil, P Sam Zhang, Yiran Stranisci, Marco Antonio Abdulmumin, Idris Alaçam, Özge Acartürk, Cengiz Jabr, Aisha Anwar, Saba Ayele, Abinew Ali Tutubalina, Elena Htet, Aung Kyaw Wang, Xintong Thapa, Surendrabikram Chakraborty, Tanmoy Kodati, Dheeraj Moradizeyveh, Sahar Alam, Firoj Thu, Ye Kyaw Parida, Shantipriya Qazi, Ihsan Ayyub Wanzare, Lilian Onyango, Nelson Odhiambo Siro, Clemencia Ahmad, Ibrahim Said Ali, Adem Chanie Semmann, Martin Biemann, Chris Muhammad, Shamsuddeen Hassan Yimam, Seid Muhie Computation and Language 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 sub-tasks: (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 submission on Codabench. We received final submissions from 67 teams and 73 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 of this task is publicly available. |
| title | SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2604.06817 |