APPReddit: a Corpus of Reddit Posts Annotated for Appraisal
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Abstract (arXiv)
Despite the large number of computational resources for emotion recognition, there is a lack of data sets relying on appraisal models. According to Appraisal theories, emotions are the outcome of a multi-dimensional evaluation of events. In this paper, we present APPReddit, the first corpus of non-experimental data annotated according to this theory. After describing its development, we compare our resource with enISEAR, a corpus of events created in an experimental setting and annotated for appraisal. Results show that the two corpora can be mapped notwithstanding different typologies of data and annotations schemes. A SVM model trained on APPReddit predicts four appraisal dimensions without significant loss. Merging both corpora in a single training set increases the prediction of 3 out of 4 dimensions. Such findings pave the way to a better performing classification model for appraisal prediction.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 5 of its 47 references that are in the map. First posted on arXiv 31 May 2022.
Builds on
5 of 47 references.
References · 5
- 2017DailyDialog: A Manually Labelled Multi-turn Dialogue Datasetcited by 652
- 2022EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysiscited by 76
- 2020Appraisal Theories for Emotion Classification in Textcited by 28
- 2019Crowdsourcing and Validating Event-focused Emotion Corpora for German and Englishcited by 25
- 2021Emotion-Aware, Emotion-Agnostic, or Automatic: Corpus Creation Strategies to Obtain Cognitive Event Appraisal Annotationscited by 6
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Citing papers per year: 2022: 2; 2023: 3; 2024: 0; 2025: 2.
7 papers.
- 2022Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Predictioncited by 46
- 2022Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corporacited by 13
- 2023Where are We in Event-centric Emotion Analysis? Bridging Emotion Role Labeling and Appraisal-based Approachescited by 7
- 2023Automatic Emotion Experiencer Recognitioncited by 1
- 2025Why Robots Are Bad at Detecting Their Mistakes: Limitations of Miscommunication Detection in Human-Robot Dialoguecited by 1
- 2023Topic Bias in Emotion Classificationcited by 0
- 2025Donate or Create? Comparing Data Collection Strategies for Emotion-labeled Multimodal Social Media Postscited by 0
- 2025Why Robots Are Bad at Detecting Their Mistakes: Limitations of Miscommunication Detection in Human-Robot Dialogue25 Jun 2025
- 2025Donate or Create? Comparing Data Collection Strategies for Emotion-labeled Multimodal Social Media Posts30 May 2025
- 2023Topic Bias in Emotion Classification14 Dec 2023
- 2023Where are We in Event-centric Emotion Analysis? Bridging Emotion Role Labeling and Appraisal-based Approaches5 Sep 2023
- 2023Automatic Emotion Experiencer Recognition26 May 2023
- 2022Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corpora14 Sep 2022
- 2022Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Prediction10 Jun 2022