Publication:
PROTEST-ER: retraining BERT for protest event extraction

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dc.conference.dateAUG 05-06, 2021
dc.conference.locationELECTR NETWORK
dc.conference.organizer4th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text (CASE)
dc.contributor.coauthorCaselli, Tommaso
dc.contributor.coauthorBasile, Angelo
dc.contributor.departmentDepartment of Sociology
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.facultymemberNo
dc.contributor.kuauthorHürriyetoğlu, Ali
dc.contributor.kuauthorMutlu, Osman
dc.contributor.schoolcollegeinstituteCollege of Social Sciences and Humanities
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-09T22:50:00Z
dc.date.issued2021
dc.description.abstractWe analyze the effect of further pre-training BERT with different domain specific data as an unsupervised domain adaptation strategy for event extraction. Portability of event extraction models is particularly challenging, with large performance drops affecting data on the same text genres (e.g., news). We present PROTEST-ER, a retrained BERT model for protest event extraction. PROTEST-ER outperforms a corresponding generic BERT on out-of-domain data of 8.1 points. Our best performing models reach 51.91-46.39 F1 across both domains.
dc.description.fulltextNo
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.peerreviewstatusN/A
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuEU
dc.description.sponsorshipEuropean Research Council (ERC) [714868]; Horizon 2020 Framework Programme
dc.description.studentonlypublicationNo
dc.description.studentpublicationYes
dc.description.versionN/A
dc.identifier.embargoN/A
dc.identifier.endpage19
dc.identifier.grantno714868
dc.identifier.isbn9781954085794
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-85119310309
dc.identifier.startpage12
dc.identifier.urihttps://hdl.handle.net/20.500.14288/6579
dc.identifier.wos000694853100004
dc.keywordsExtraction modeling
dc.keywords Events extractions
dc.keywordsNatural language processing
dc.keywordsDomain adaptation
dc.language.isoeng
dc.publisherAssociation for Computational Linguistics (ACL)
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofCase 2021: The 4th Workshop On Challenges And Applications Of Automated Extraction Of Socio-Political Events From Text (Case)
dc.relation.openaccessN/A
dc.rightsN/A
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectLinguistics
dc.titlePROTEST-ER: retraining BERT for protest event extraction
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorMutlu, Osman
local.contributor.kuauthorHürriyetoğlu, Ali
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