Exploring the Intersection of Big Data and Legal Analytics: A Survey of its Application in the Legal Industry

Abstract

Over the last decade, we have witnessed exponential growth in the usage of Big Data in a wide range of domains such as the entertainment industry, sports industry, financial industry etc. The legal industry is starting to take notice of Big Data analytics in their field. Lawyers have been using big data analytics tools for their daily purposes which include billing, marketing and customer relations functions. For the survey, "Legal Analytics" was defined as software that uses artificial intelligence to search through massive amounts of data and identify trends that are useful to lawyers. The connection between Big Data (BD) and law can be visualised in several ways. More and more law firms are turning to Big Data to identify which cases are likely to be straightforward and which cases will have hidden hurdles to overcome. In this paper, we have attempted to compare and take a deeper look at some of the algorithms and platforms built and developed for data analytics, namely Auto-Regressive Integrated Moving Average (ARIMA), Structural Equation Modelling (SEM), Long Short – Term Memory (LSTM) and a platform known as many Laws which is used for fetching queries and specific laws through a vast database of European laws and regulations. We have further studied how different parameters have affected the results in the case of models such as ARIMA and have taken a look into a text extractor architecture that incorporates the use of LSTM in one of its layers to extract relevant information.