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 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.

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Publication Details

Journal
Language Resources and Evaluation
Published
2025-06-06
DOI
https://doi.org/10.1007/s10579-025-09828-1
Citations
2
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
4.96
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article

Review of recent emotion-annotated text corpora and resources

Anna Koufakou, Elijah Nieves
2 citations
Language Resources and Evaluation
Sentiment Analysis and Opinion Mining
4.96
article

Review of recent emotion-annotated text corpora and resources

Anna Koufakou, Elijah Nieves
article en
2 citations

Abstract

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.

Language Resources and EvaluationVol. 59(4)
Florida Gulf Coast University (US)
Openalex Percentile: Top 5%
Sentiment Analysis and Opinion Mining
4.96
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Review of recent emotion-annotated text corpora and resources — Anna Koufakou, Elijah Nieves · Language Resources and Evaluation (2025) | TGRS Research Map | TGRS