APPReddit: a Corpus of Reddit Posts Annotated for Appraisal

TL;DR

This paper introduces APPReddit, a novel corpus of Reddit posts annotated for appraisal-based emotion analysis, demonstrating its effectiveness for training models and improving emotion classification accuracy.

Contribution

It presents the first non-experimental, appraisal-annotated Reddit corpus and compares it with experimental data, enhancing emotion prediction models.

Findings

SVM trained on APPReddit predicts four appraisal dimensions effectively.

Merging APPReddit with enISEAR improves prediction of three out of four dimensions.

The corpus enables better emotion classification based on appraisal theory.

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.