Sentiment analysis is one of the fastest growing research areas in computer
science, making it challenging to keep track of all the activities in the area.
We present a computer-assisted literature review, where we utilize both text
mining and qualitative coding, and analyze 6,996 papers from Scopus. We find
that the roots of sentiment analysis are in the studies on public opinion
analysis at the beginning of 20th century and in the text subjectivity analysis
performed by the computational linguistics community in 1990's. However, the
outbreak of computer-based sentiment analysis only occurred with the
availability of subjective texts on the Web. Consequently, 99% of the papers
have been published after 2004. Sentiment analysis papers are scattered to
multiple publication venues, and the combined number of papers in the top-15
venues only represent ca. 30% of the papers in total. We present the top-20
cited papers from Google Scholar and Scopus and a taxonomy of research topics.
In recent years, sentiment analysis has shifted from analyzing online product
reviews to social media texts from Twitter and Facebook. Many topics beyond
product reviews like stock markets, elections, disasters, medicine, software
engineering and cyberbullying extend the utilization of sentiment analysis

通过计算机辅助文献综述，发现情感分析的起源可以追溯到 20 世纪初进行的公共舆情分析和 20 世纪 90 年代的文本主体性分析，但基于网络上的主观文本的情感分析爆发是在 2004 年之后。最近几年，情感分析已经从分析在线产品评论转移到分析来自 Twitter 和 Facebook 等社交媒体的文本。感情分析的应用还扩展到股票市场、选举、灾害、医学、软件工程和网络欺凌等许多主题。