Extended Multilingual Protest News Detection - Shared Task 1, CASE 2021 and 2022

Hürriyetoğlu, Ali; Mutlu, Osman; Duruşan, Fırat; Uca, Onur; Gürel, Alaeddin; Radford, Benjamin J.; Dai, Yaoyao; Hettiarachchi, Hansi; Stoehr, Niklas; Nomoto, Tadashi; Slavcheva, Milena; Vargas, Francielle Alves; Javid, Aaqib; Fatih, Beyhan,; Yörük, Erdem

doi:10.18653/v1/2022.case-1.31

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“…We tackle the task in four steps and hope state-of-the-art approaches will yield optimal results. This shared task was announced as a re-run of the same tasks from CASE 2021 (Hürriyetoglu et al, 2021a) and CASE 2022 (Hürriyetoglu et al, 2022a). Although it attracted some interest, we did not receive any task description papers for this edition.…”

Section: Task 1: Multilingual Protest News Detectionmentioning

confidence: 99%

Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021): Workshop and Shared Task Report

Hürriyetoğlu¹,

Tanev²,

Zavarella³

et al. 2021

Proceedings of the 4th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events From Text (CAS

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This workshop is the fourth issue of a series of workshops on automatic extraction of sociopolitical events from news, organized by the Emerging Market Welfare Project, with the support of the Joint Research Centre of the European Commission and with contributions from many other prominent scholars in this field. The purpose of this series of workshops is to foster research and development of reliable, valid, robust, and practical solutions for automatically detecting descriptions of sociopolitical events, such as protests, riots, wars and armed conflicts, in text streams. This year workshop contributors make use of the stateof-the-art NLP technologies, such as Deep Learning, Word Embeddings and Transformers and cover a wide range of topics from text classification to news bias detection. Around 40 teams have registered and 15 teams contributed to three tasks that are i) multilingual protest news detection, ii) fine-grained classification of socio-political events, and iii) discovering Black Lives Matter protest events. The workshop also highlights two keynote and four invited talks about various aspects of creating event data sets and multi-and cross-lingual machine learning in few-and zero-shot settings.

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Section: Task 1: Multilingual Protest News Detectionmentioning

confidence: 99%