Short-term meaning shift: a distributional exploration

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To access the full text documents, please follow this link: http://hdl.handle.net/10230/42449

dc.contributor.author	Boleda, Gemma
dc.contributor.author	Del Tredici, Marco
dc.contributor.author	Fernández, Raquel
dc.date	2019
dc.identifier.citation	Del Tredici M, Fernández R, Boleda G. Short-term meaning shift: a distributional exploration. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies; 2019 Jun 2-7; Minneapolis, United States of America. Stroudsburg (PA): ACL; 2019. p. 2069–75.
dc.identifier.uri	http://hdl.handle.net/10230/42449
dc.format	application/pdf
dc.language.iso	eng
dc.publisher	ACL (Association for Computational Linguistics)
dc.relation	Proceedings of the 2019 ; 2019 Jun 2-7; Minneapolis, United States of America. Stroudsburg (PA): ACL; 2019. p. 2069–75.
dc.relation	info:eu-repo/grantAgreement/EC/H2020/715154
dc.rights	© ACL, Creative Commons Attribution 4.0 License
dc.rights	https://creativecommons.org/licenses/by/4.0/
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Semantic change
dc.subject	Meaning shift
dc.subject	Distributional semantics
dc.subject	Deep learning
dc.subject	Online communities
dc.subject	Short-time meaning shift
dc.subject	Computational semantics
dc.subject	Computational linguistics
dc.title	Short-term meaning shift: a distributional exploration
dc.type	info:eu-repo/semantics/conferenceObject
dc.type	info:eu-repo/semantics/publishedVersion
dc.description.abstract	_
dc.description.abstract	Comunicació presentada a la Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2019), celebrada els dies 2 a 7 de juny de 2019 a Minneapolis, Estats Units d'Amèrica.
dc.description.abstract	We present the first exploration of meaning shift over short periods of time in online communities using distributional representations. We create a small annotated dataset and use it to assess the performance of a standard model for meaning shift detection on shortterm meaning shift. We find that the model has problems distinguishing meaning shift from referential phenomena, and propose a measure of contextual variability to remedy this.
dc.description.abstract	The research carried out by the Amsterdam section of the team was partially funded by the Netherlands Organisation for Scientific Research (NWO) under VIDI grant no. 276-89-008, Asymmetry in Conversation. This project has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No 715154), and from the Spanish Ramón y Cajal programme (grant RYC-2015-18907).

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