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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Bibliographic Details
Published inJournal of information science Vol. 44; no. 5; pp. 594 - 607
Main Authors Liu, Yi-Hung, Chen, Yen-Liang
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.10.2018
Bowker-Saur Ltd
Subjects
Classification
Court decisions
Data mining
Feature extraction
Information technology
Litigation
Predictions
Sentiment analysis
judgement classification
support vector machines (SVM)
text mining
Criminal precedent
sentiment analysis
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Summary: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.
ISSN:0165-5515
1741-6485
DOI:10.1177/0165551517722741