mlsanityData to 14 Oct 2026

APPReddit: a Corpus of Reddit Posts Annotated for Appraisal

arXiv 2205.15627 ↗First posted 31 May 2022cs.CLcited by 7

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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

  1. 2017DailyDialog: A Manually Labelled Multi-turn Dialogue Datasetcited by 652
  2. 2022EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysiscited by 76
  3. 2020Appraisal Theories for Emotion Classification in Textcited by 28
  4. 2019Crowdsourcing and Validating Event-focused Emotion Corpora for German and Englishcited by 25
  5. 2021Emotion-Aware, Emotion-Agnostic, or Automatic: Corpus Creation Strategies to Obtain Cognitive Event Appraisal Annotationscited by 6

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Cited by year

Citing papers per year: 2022: 2; 2023: 3; 2024: 0; 2025: 2.

7 papers.