Sarcasm detection with BERT

Scola, Elsa; Segura-Bedmar, Isabel

Publication:
Sarcasm detection with BERT

dc.affiliation.dpto	UC3M. Departamento de Informática	es
dc.affiliation.grupoinv	UC3M. Grupo de Investigación: Human Language and Accessibility Technologies (HULAT)	es
dc.contributor.author	Scola, Elsa
dc.contributor.author	Segura-Bedmar, Isabel
dc.contributor.funder	Comunidad de Madrid	es
dc.contributor.funder	Universidad Carlos III de Madrid	es
dc.date.accessioned	2022-06-24T08:28:40Z
dc.date.available	2022-06-24T08:28:40Z
dc.date.issued	2021-09-23
dc.description.abstract	Sarcasm is often used to humorously criticize something or hurt someone's feelings. Humans often have difficulty in recognizing sarcastic comments since we say the opposite of what we really mean. Thus, automatic sarcasm detection in textual data is one of the most challenging tasks in Natural Language Processing (NLP). It has also become a relevant research area due to its importance in the improvement of sentiment analysis. In this work, we explore several deep learning models such as Bidirectional Long Short-Term Memory (BiLSTM) and Bidirectional Encoder Representations from Transformers (BERT) to address the task of sarcasm detection. While most research has been conducted using social media data, we evaluate our models using a news headlines dataset. To the best of our knowledge, this is the first study that applies BERT to detect sarcasm in texts that do not come from social media. Experiment results show that the BERT-based approach overcomes the state-of-the-art on this type of dataset.	en
dc.description.sponsorship	This work has been supported by the Madrid Government (Comunidad de Madrid) under the Multiannual Agreement with UC3M in the line of “Fostering Young Doctors Research”(NLP4RARE-CM-UC3M), as well as in the line of “Excellence of University Professors”(EPUC3M17), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).	en
dc.identifier.bibliographicCitation	Scola, E., Segura-Bedmar, I. (2021). Sarcasm detection with BERT. Procesamiento del Lenguaje Natura, 67, pp. 13-25.	en
dc.identifier.doi	https://doi.org/10.26342/2021-67-1
dc.identifier.issn	1135-5948
dc.identifier.publicationfirstpage	13
dc.identifier.publicationissue	67
dc.identifier.publicationlastpage	25
dc.identifier.publicationtitle	Procesamiento de Lenguaje Natural	es
dc.identifier.uri	https://hdl.handle.net/10016/35272
dc.identifier.uxxi	AR/0000030878
dc.language.iso	eng
dc.publisher	Sociedad Española para el Procesamiento del Lenguaje Natural	es
dc.relation.projectID	Comunidad de Madrid. NLP4Rare-CM-UC3M	es
dc.relation.publisherversion	http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6373
dc.rights	© 2021 Sociedad Española para el Procesamiento del Lenguaje Natural	es
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRights	open access	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.eciencia	Informática	es
dc.subject.other	sarcasm detection	en
dc.subject.other	deep learning	en
dc.subject.other	bilstm	en
dc.subject.other	BERT	en
dc.title	Sarcasm detection with BERT	en
dc.type	research article	*
dc.type.hasVersion	AM	*
dspace.entity.type	Publication