APPReddit: a Corpus of Reddit Posts Annotated for Appraisal

Marco Antonio Stranisci, Simona Frenda, Eleonora Ceccaldi, Valerio Basile, Rossana Damiano, Viviana Patti


Abstract
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.
Anthology ID:
2022.lrec-1.406
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
3809–3818
Language:
URL:
https://aclanthology.org/2022.lrec-1.406
DOI:
Bibkey:
Cite (ACL):
Marco Antonio Stranisci, Simona Frenda, Eleonora Ceccaldi, Valerio Basile, Rossana Damiano, and Viviana Patti. 2022. APPReddit: a Corpus of Reddit Posts Annotated for Appraisal. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 3809–3818, Marseille, France. European Language Resources Association.
Cite (Informal):
APPReddit: a Corpus of Reddit Posts Annotated for Appraisal (Stranisci et al., LREC 2022)
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PDF:
https://aclanthology.org/2022.lrec-1.406.pdf