Abstract
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.