APPReddit: a Corpus of Reddit Posts Annotated for Appraisal
This provides a new resource for researchers in computational linguistics and emotion analysis, though it is incremental as it builds on existing appraisal theories and datasets.
The authors tackled the lack of non-experimental datasets for appraisal-based emotion recognition by creating APPReddit, a corpus of Reddit posts annotated according to appraisal theories, and found that merging it with an existing experimental corpus improved prediction for 3 out of 4 appraisal dimensions.
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.