A two-phase sentiment analysis approach for judgement prediction

Factual scenario analysis of a judgement is critical to judges during sentencing. With the increasing number of legal cases, professionals typically endure heavy workloads on a daily basis. Although a few previous studies have applied information technology to legal cases, according to our research,...

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Published in:Journal of information science 2018-10, Vol.44 (5), p.594-607
Main Authors: Liu, Yi-Hung, Chen, Yen-Liang
Format: Article
Language:English
Subjects:
Classification
Court decisions
Data mining
Feature extraction
Information technology
Litigation
Predictions
Sentiment analysis
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description Factual scenario analysis of a judgement is critical to judges during sentencing. With the increasing number of legal cases, professionals typically endure heavy workloads on a daily basis. Although a few previous studies have applied information technology to legal cases, according to our research, no prior studies have predicted a pending judgement using legal documents. In this article, we introduce an innovative solution to predict relevant rulings. The proposed approach employs text mining methods to extract features from precedents and applies a text classifier to automatically classify judgements according to sentiment analysis. This approach can assist legal experts or litigants in predicting possible judgements. Experimental results from a judgement data set reveal that our approach is a satisfactory method for judgement classification.
doi_str_mv 10.1177/0165551517722741
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source Library & Information Science Abstracts (LISA); SAGE
subjects Classification
Court decisions
Data mining
Feature extraction
Information technology
Litigation
Predictions
Sentiment analysis
title A two-phase sentiment analysis approach for judgement prediction
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