Publication:
Challenges and applications of automated extraction of socio-political events from text (case 2021): workshop and shared task report

dc.contributor.coauthorTanev, Hristo
dc.contributor.coauthorZavarella, Vanni
dc.contributor.coauthorPiskorski, Jakub
dc.contributor.coauthorYeniterzi, Reyyan
dc.contributor.coauthorVillavicencio, Aline
dc.contributor.departmentDepartment of Sociology
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorHürriyetoğlu, Ali
dc.contributor.kuauthorMutlu, Osman
dc.contributor.kuauthorYörük, Erdem
dc.contributor.kuauthorYüret, Deniz
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteCollege of Social Sciences and Humanities
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-10T00:06:37Z
dc.date.issued2021
dc.description.abstractThis 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 state-of-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.
dc.description.indexedbyWOS
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipEuropean Research Council (ERC) [714868] The authors from Koc University were funded by the European Research Council (ERC) Starting Grant 714868 awarded to Dr. Erdem Yoruk for his project Emerging Welfare.
dc.identifier.isbn978-1-954085-79-4
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-85110564871
dc.identifier.urihttps://hdl.handle.net/20.500.14288/16643
dc.identifier.wos694853100001
dc.keywordsAutomated extraction
dc.keywordsSocio-political events
dc.language.isoeng
dc.publisherAssociation for Computational Linguistics (ACL)
dc.relation.ispartofCase 2021: The 4th Workshop On Challenges and Applications of Automated Extraction of Socio-Political Events From Text (Case)
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectInterdisciplinary applications
dc.subjectLinguistics
dc.titleChallenges and applications of automated extraction of socio-political events from text (case 2021): workshop and shared task report
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorHürriyetoğlu, Ali
local.contributor.kuauthorYörük, Erdem
local.contributor.kuauthorMutlu, Osman
local.contributor.kuauthorYüret, Deniz
local.publication.orgunit1College of Social Sciences and Humanities
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Sociology
local.publication.orgunit2Department of Computer Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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