University of Oulu

Mika V. Mäntylä, Daniel Graziotin, Miikka Kuutila, The evolution of sentiment analysis - A review of research topics, venues, and top cited papers, Computer Science Review, Volume 27, 2018, Pages 16-32, ISSN 1574-0137, https://doi.org/10.1016/j.cosrev.2017.10.002

The evolution of sentiment analysis : a review of research topics, venues, and top cited papers

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Author: Mäntylä, Mika V.1; Graziotin, Daniel2; Kuutila, Miikka1
Organizations: 1M3S, ITEE, University of Oulu, Finland
2Institute of Software Technology, University of Stuttgart, Germany
Format: article
Version: accepted version
Access: embargoed
Persistent link: http://urn.fi/urn:nbn:fi-fe2019060318264
Language: English
Published: Elsevier, 2018
Publish Date: 2020-02-28
Description:

Abstract

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 6996 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.

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Series: Computer science review
ISSN: 1574-0137
ISSN-E: 1876-7745
ISSN-L: 1574-0137
Volume: 27
Pages: 16 - 32
DOI: 10.1016/j.cosrev.2017.10.002
OADOI: https://oadoi.org/10.1016/j.cosrev.2017.10.002
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Subjects:
Funding: The first and third author have been partially supported by the Academy of Finland grant 298020. The second author has been supported by the Alexander von Humboldt (AvH) Foundation.
Academy of Finland Grant Number: 298020
Detailed Information: 298020 (Academy of Finland Funding decision)
Copyright information: © 2017 Elsevier Inc. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
  https://creativecommons.org/licenses/by-nc-nd/4.0/