Natural Language Processing in Big Data Context: A Bibliographic Analysis
(A2023-114080)

AUTHORS

Sergi Pons, Universitat de Barcelona; Laura Saez-Ortuno, University of Barcelona

ABSTRACT

In recent decades and especially in the last years, society is witnessing an exponential acceleration of digital solutions and digital democratization. In addition, Natural Language Processing (NLP) offers a wide range of possibilities in terms of research due to the better accuracy and improvement of Machine Learning (ML) and Deep Learning (DL) models. These models have shown improvements due to the enhance of the current tools to overcome the challenges of Big Data. ML and DL are hot topics widely covered in the literature through conceptual and empirical approaches. Nevertheless, it is widely covered in computing, linguistics, or natural sciences and rarely in social sciences. Therefore, the aim of this study is to contextualize the potential of NLP in the business field as well as to present some case studies. The conclusions from the analyzed articles shown how these methods perform with a good accuracy, being the DL methods the more precise to predict a range of outcomes.