Review of recent emotion-annotated text corpora and resources.
Automated Emotion Recognition in text is a challenging application that has attracted significant interest. This paper addresses the significant need to study recently-introduced text corpora labeled for emotion recognition tasks. In this paper, we detail and analyze 30 text corpora introduced since...
| Publicado en: | Language Resources & Evaluation Vol. 59; no. 4; pp. 4313 - 4348 |
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| Autores principales: | , |
| Formato: | Artículo |
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Springer Nature
Dec2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=189912017&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 189912017 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Dec2025 vid: 59 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 189912017 10.1007/s10579-025-09828-1 ppf: 4313 ppct: 35 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.1MB tig: atl: Review of recent emotion-annotated text corpora and resources. aug: au: Koufakou, Anna Nieves, Elijah affil: https://ror.org/05tc5bm31 Department of Computing and Software Engineering, U.A. Whitaker College of Engineering, Florida Gulf Coast University, 33965, Fort Myers, FL, USA su: Emotion recognition Corpora Computational linguistics Acquisition of data Annotations Information resources sug: subj: Emotion recognition Corpora Computational linguistics Acquisition of data Annotations Information resources keyword: Affective computing Emotion corpora Emotion detection NLP Text annotation ab: Automated Emotion Recognition in text is a challenging application that has attracted significant interest. This paper addresses the significant need to study recently-introduced text corpora labeled for emotion recognition tasks. In this paper, we detail and analyze 30 text corpora introduced since 2018, offering insights into their sources, languages, emotion labels, annotation methodologies, availability, size, and other characteristics. We also summarize previous models and results on emotion recognition using the corpora in our study, and share recent events such as shared tasks and other resources such as lexicons. Finally, we offer a discussion of related practices and challenges. Our aim is for this paper and the accompanying online repository to function as a comprehensive resource, offering researchers a centralized hub for accessing related links, information, comparisons, and more, while also educating the research community on current practices for data collection, annotation, and usage in emotion recognition. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2025. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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