  Recent advances in machine learning have led to computer systems that are
human-like in behaviour. Sentiment analysis, the automatic determination of
emotions in text, is allowing us to capitalize on substantial previously
unattainable opportunities in commerce, public health, government policy,
social sciences, and art. Further, analysis of emotions in text, from news to
social media posts, is improving our understanding of not just how people
convey emotions through language but also how emotions shape our behaviour.
This article presents a sweeping overview of sentiment analysis research that
includes: the origins of the field, the rich landscape of tasks, challenges, a
survey of the methods and resources used, and applications. We also discuss
discuss how, without careful fore-thought, sentiment analysis has the potential
for harmful outcomes. We outline the latest lines of research in pursuit of
fairness in sentiment analysis.
