论文标题
基于BERT的合奏，用于建模对话社交媒体文本中的披露和支持
BERT-based Ensembles for Modeling Disclosure and Support in Conversational Social Media Text
论文作者
论文摘要
人们对了解人类如何发起和举行对话的兴趣越来越大。对对话的情感理解重点是说话者如何利用情感对情况和彼此做出反应的问题。在CL-AFF共享任务中，组织者发布了#OffMyChest数据集，其中包含随意和供认对话中的reddit评论，标有其披露和支持特征。在本文中，我们介绍了一个预测的集合模型，利用了填充的上下文化词嵌入Roberta和Albert。我们表明，我们的模型在所有考虑的指标中都优于基本模型，从而在F1分数中提高了$ 3 \％$。我们进一步进行统计分析，并概述对给定数据集的更深入的见解，同时提供对数据集影响的新特征。
There is a growing interest in understanding how humans initiate and hold conversations. The affective understanding of conversations focuses on the problem of how speakers use emotions to react to a situation and to each other. In the CL-Aff Shared Task, the organizers released Get it #OffMyChest dataset, which contains Reddit comments from casual and confessional conversations, labeled for their disclosure and supportiveness characteristics. In this paper, we introduce a predictive ensemble model exploiting the finetuned contextualized word embeddings, RoBERTa and ALBERT. We show that our model outperforms the base models in all considered metrics, achieving an improvement of $3\%$ in the F1 score. We further conduct statistical analysis and outline deeper insights into the given dataset while providing a new characterization of impact for the dataset.
