Applications and Challenges of Sentiment Analysis in Real-life Scenarios

Diptesh Kanojia, Aditya Joshi

Published 2023-01-24Version 1

Sentiment analysis has benefited from the availability of lexicons and benchmark datasets created over decades of research. However, its applications to the real world are a driving force for research in SA. This chapter describes some of these applications and related challenges in real-life scenarios. In this chapter, we focus on five applications of SA: health, social policy, e-commerce, digital humanities and other areas of NLP. This chapter is intended to equip an NLP researcher with the `what', `why' and `how' of applications of SA: what is the application about, why it is important and challenging and how current research in SA deals with the application. We note that, while the use of deep learning techniques is a popular paradigm that spans these applications, challenges around privacy and selection bias of datasets is a recurring theme across several applications.