• Corpus ID: 226226405

Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting

@inproceedings{Ratnayaka2020EffectiveAT,
  title={Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting},
  author={Gathika Ratnayaka and Nisansa de Silva and Amal Shehan Perera and Ramesh Pathirana},
  booktitle={Pacific Asia Conference on Language, Information and Computation},
  year={2020}
}
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… 

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