Unified Legal Party Based Sentiment Analysis Pipeline

Abstract

The rapid growth of text corpora across various domains has emerged a need and an opportunity to leverage Natural Language Processing to automate and efficiently streamline tedious manual tasks. Legal domain is one such text rich domain which suffers a rapid growth of text corpora and requirement for natural language processing applications. In the pursuit of automating the prediction of the winning party of a court case among other usages, analysing sentiment in a party wise manner is beneficial for legal professionals. The two main sub-tasks in this process is to identify parties in a court case and afterwards analysing the respective sentiment towards each party. In this study we discuss the unification of two such models capable of doing the two task into a single pipeline to perform party based sentiment analysis efficiently.