A Survey of Research on Data Analytics-Based Legal Tech

Abstract

Data analytics provides important tools and methods for processing the data generated during legal services. This paper aims to provide a systematic survey of the research papers on the application of quantitative data analytics algorithms in the legal domain. To this end, relevant research papers were collected and used to analyze topics and trends of research on data analytics-based Legal Tech. The key findings of this paper are as follows. Firstly, the number of research papers about Legal Tech has increased dramatically recently. Secondly, the application of supervised learning techniques to legal judgment data is a very popular approach in this research area. Thirdly, preprocessing legal documents is a very important procedure as many legal documents exist in text form. Fourthly, artificial neural networks and their variations are widely used in research on data analytics-based Legal Tech. Fifthly, data analytics-based Legal Tech is a multidisciplinary research topic related to computer science and social science, etc.