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.
翻译:最近机器学习的进展导致计算机系统在行为上与人相似。感知分析、文字中情感的自动确定,使我们得以利用商业、公共卫生、政府政策、社会科学和艺术等领域以前无法利用的大量机会。此外,从新闻到社交媒体文章,对文字中的情感分析正在使我们更好地了解不仅人们如何通过语言传递情感,而且情感如何影响我们的行为。这篇文章概述了情绪分析研究,其中包括:实地的起源、任务、挑战的丰富背景、对所用方法和资源以及应用的调查。我们还讨论在没有审慎的先入为主的情况下,情绪分析如何产生有害的结果。我们概述了追求情绪分析公平的最新研究路线。