论文标题
批准：评估注释的Reddit职位语料库
APPReddit: a Corpus of Reddit Posts Annotated for Appraisal
论文作者
论文摘要
尽管有大量的情感识别计算资源，但缺乏依赖评估模型的数据集。根据评估理论，情感是对事件的多维评估的结果。在本文中，我们介绍了批准的，这是根据该理论注释的第一个非实验数据的语料库。在描述了它的发展之后，我们将资源与Enisear进行了比较，Enisear是在实验环境中创建的事件和评估注释。结果表明，尽管数据和注释方案的类型不同，但可以映射这两个语料库。经过批准的培训的SVM模型可以预测四个评估维度而不会造成大量损失。在单个培训集中合并两个语料库可提高4个维度中3个的预测。此类发现为评估预测的更好性能分类模型铺平了道路。
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.
