The evolution of sentiment analysis - A review of research topics, venues, and top cited papers
By Mika V. Mäntylä, Daniel Graziotin, Miikka Kuutila. Computer Science Review, 2016
640 citations recorded by the source corpus.
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
Subfields: Artificial Intelligence, General Social Sciences, Social Psychology
View Paper: https://www.semanticscholar.org/paper/2bba425a80880d80ca4e3511677852bcb3990fe5
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In Artificial Intelligence
Citations in the corpus
- Word Embeddings in Sentiment Analysis (2018, background): “As reported by Mäntylä et al. (2016) the number of papers on this subject has increased significantly in the first two decades of 21st century, as well as the extent of its applications.”