论文标题
在低资源设置中为法律领域开发情感注释者的有效方法
Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting
论文作者
论文摘要
分析法律意见中提供的法律意见的情感可以促进几种用例，例如法律判决预测，矛盾的陈述识别和基于政党的情感分析。但是，由于资源限制（例如缺乏域特定标记的数据和域专业知识），开发法律领域特定情感注释者的任务是具有挑战性的。在这项研究中，我们提出了新技术，这些技术可用于开发法律领域的情感注释者，同时最大程度地减少对数据的手动注释的需求。
Analyzing the sentiments of legal opinions available in Legal Opinion Texts can facilitate several use cases such as legal judgement prediction, contradictory statements identification and party-based sentiment analysis. However, the task of developing a legal domain specific sentiment annotator is challenging due to resource constraints such as lack of domain specific labelled data and domain expertise. In this study, we propose novel techniques that can be used to develop a sentiment annotator for the legal domain while minimizing the need for manual annotations of data.
