2016/12/31 by Mika V. Mäntylä, Mika Viking Mäntylä, Daniel Graziotin +1
Computer Science · Psychology · Social Sciences · #Computational and Text Analysis Methods #Computational linguistics #Mental Health via Writing #Product (mathematics) #Qualitative analysis #Scopus #Sentiment Analysis and Opinion Mining #Sentiment analysis #Social media #Subjectivity #Taxonomy (biology) #cs.CL #cs.DL #cs.SI
paper · pdf · doi:10.1016/j.cosrev.2017.10.002
published as Computer Science Review, Volume 27, February 2018, Pages 16-32 · 29 pages, 14 figures
openalex created_date 2017/01/13 · arxiv created 2017/11/21 · openalex publication_date 2017/11/21 · arxiv updated 2017/11/22 · openalex updated_date 2026/08/06
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