Natural Language Processing in Advertising – A Systematic Literature Review

Abstract

Computational or programmatic advertising is the new way to advertise products and services online and in real-time. In this emerging type of advertising, Natural language processing (NLP) is a powerful tool for intelligently targeting and placing advertisements at the right time and in the right place for the right audience in a very short period. This study systematically reviewed journal articles, book chapters, and conference proceedings for the last ten years to find out what are the uses, approaches, and challenges that the researchers have been recently facing in making use of natural language processing techniques in the domain of advertising. It is found that in the majority of studies, information extraction and sentiment analysis are still the main focus areas. Only a small number of advanced artificial intelligence (AI) techniques, such as deep learning and speech synthesis, are used. In addition, most of the studies are based on traditional forms of advertising (such as search engines, websites, and job listings), excluding the newer forms of mobile and app-based advertising. The ongoing challenge in the current literature is applying natural language processing to automatically target advertisements.